{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 一、已知多变量对连续单变量的预测\n",
    "\n",
    "**目标变量**：Temperature (C)（温度）\n",
    "**输入特征**：所有其他特征，包括日期、分类变量和数值变量。\n",
    "\n",
    "## 1. 线性回归模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 96429 entries, 0 to 96428\n",
      "Data columns (total 41 columns):\n",
      " #   Column                                       Non-Null Count  Dtype  \n",
      "---  ------                                       --------------  -----  \n",
      " 0   Temperature (C)                              96429 non-null  float64\n",
      " 1   Apparent Temperature (C)                     96429 non-null  float64\n",
      " 2   Humidity                                     96429 non-null  float64\n",
      " 3   Wind Speed (km/h)                            96429 non-null  float64\n",
      " 4   Wind Bearing (degrees)                       96429 non-null  float64\n",
      " 5   Visibility (km)                              96429 non-null  float64\n",
      " 6   Pressure (millibars)                         96429 non-null  float64\n",
      " 7   Year                                         96429 non-null  int32  \n",
      " 8   Month                                        96429 non-null  int32  \n",
      " 9   Day                                          96429 non-null  int32  \n",
      " 10  Hour                                         96429 non-null  int32  \n",
      " 11  Weekday                                      96429 non-null  int32  \n",
      " 12  Summary_Breezy                               96429 non-null  bool   \n",
      " 13  Summary_Breezy and Dry                       96429 non-null  bool   \n",
      " 14  Summary_Breezy and Foggy                     96429 non-null  bool   \n",
      " 15  Summary_Breezy and Mostly Cloudy             96429 non-null  bool   \n",
      " 16  Summary_Breezy and Overcast                  96429 non-null  bool   \n",
      " 17  Summary_Breezy and Partly Cloudy             96429 non-null  bool   \n",
      " 18  Summary_Clear                                96429 non-null  bool   \n",
      " 19  Summary_Dangerously Windy and Partly Cloudy  96429 non-null  bool   \n",
      " 20  Summary_Drizzle                              96429 non-null  bool   \n",
      " 21  Summary_Dry                                  96429 non-null  bool   \n",
      " 22  Summary_Dry and Mostly Cloudy                96429 non-null  bool   \n",
      " 23  Summary_Dry and Partly Cloudy                96429 non-null  bool   \n",
      " 24  Summary_Foggy                                96429 non-null  bool   \n",
      " 25  Summary_Humid and Mostly Cloudy              96429 non-null  bool   \n",
      " 26  Summary_Humid and Overcast                   96429 non-null  bool   \n",
      " 27  Summary_Humid and Partly Cloudy              96429 non-null  bool   \n",
      " 28  Summary_Light Rain                           96429 non-null  bool   \n",
      " 29  Summary_Mostly Cloudy                        96429 non-null  bool   \n",
      " 30  Summary_Overcast                             96429 non-null  bool   \n",
      " 31  Summary_Partly Cloudy                        96429 non-null  bool   \n",
      " 32  Summary_Rain                                 96429 non-null  bool   \n",
      " 33  Summary_Windy                                96429 non-null  bool   \n",
      " 34  Summary_Windy and Dry                        96429 non-null  bool   \n",
      " 35  Summary_Windy and Foggy                      96429 non-null  bool   \n",
      " 36  Summary_Windy and Mostly Cloudy              96429 non-null  bool   \n",
      " 37  Summary_Windy and Overcast                   96429 non-null  bool   \n",
      " 38  Summary_Windy and Partly Cloudy              96429 non-null  bool   \n",
      " 39  PrecipType_rain                              96429 non-null  bool   \n",
      " 40  PrecipType_snow                              96429 non-null  bool   \n",
      "dtypes: bool(29), float64(7), int32(5)\n",
      "memory usage: 9.7 MB\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "# 可视化库\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "# 机器学习库\n",
    "from sklearn.model_selection import train_test_split, GridSearchCV\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.ensemble import RandomForestRegressor\n",
    "from sklearn.metrics import mean_squared_error, mean_absolute_error, r2_score\n",
    "\n",
    "# 假设数据保存在 'weatherHistory.csv' 文件中\n",
    "data = pd.read_csv('weatherHistory.csv')\n",
    "\n",
    "\n",
    "# 将 'Formatted Date' 转换为日期时间格式\n",
    "data['Formatted Date'] = pd.to_datetime(data['Formatted Date'], utc=True)\n",
    "\n",
    "# 提取时间特征\n",
    "data['Year'] = data['Formatted Date'].dt.year\n",
    "data['Month'] = data['Formatted Date'].dt.month\n",
    "data['Day'] = data['Formatted Date'].dt.day\n",
    "data['Hour'] = data['Formatted Date'].dt.hour\n",
    "data['Weekday'] = data['Formatted Date'].dt.weekday\n",
    "\n",
    "\n",
    "# 对 'Summary' 和 'Precip Type' 进行独热编码\n",
    "data = pd.get_dummies(data, columns=['Summary', 'Precip Type'], prefix=['Summary', 'PrecipType'])\n",
    "\n",
    "# 删除原始的 'Formatted Date' 和 'Daily Summary' 列\n",
    "data = data.drop(['Formatted Date', 'Daily Summary'], axis=1)\n",
    "\n",
    "# 再次查看数据的信息\n",
    "print(data.info())\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "线性回归 模型评估结果：\n",
      "MSE: 0.8961\n",
      "RMSE: 0.9466\n",
      "MAE: 0.7406\n",
      "R² Score: 0.9902\n",
      "\n",
      "                                        Feature   Coefficient\n",
      "0                      Apparent Temperature (C)  9.338752e+00\n",
      "13                     Summary_Breezy and Foggy  1.927948e+00\n",
      "21                Summary_Dry and Mostly Cloudy  1.083557e+00\n",
      "20                                  Summary_Dry  1.021075e+00\n",
      "22                Summary_Dry and Partly Cloudy  8.539982e-01\n",
      "25                   Summary_Humid and Overcast  6.520252e-01\n",
      "2                             Wind Speed (km/h)  5.899799e-01\n",
      "24              Summary_Humid and Mostly Cloudy  4.957599e-01\n",
      "11                               Summary_Breezy  4.786590e-01\n",
      "26              Summary_Humid and Partly Cloudy  4.158095e-01\n",
      "30                        Summary_Partly Cloudy  1.692247e-01\n",
      "17                                Summary_Clear  1.301108e-01\n",
      "29                             Summary_Overcast  1.236184e-01\n",
      "28                        Summary_Mostly Cloudy  5.245805e-02\n",
      "36                   Summary_Windy and Overcast  5.018787e-02\n",
      "39                              PrecipType_snow  4.045341e-02\n",
      "7                                         Month  2.031400e-02\n",
      "6                                          Year  1.862220e-02\n",
      "10                                      Weekday  1.074433e-02\n",
      "9                                          Hour  4.041160e-03\n",
      "33                        Summary_Windy and Dry -1.665335e-16\n",
      "12                       Summary_Breezy and Dry -7.632783e-15\n",
      "4                               Visibility (km) -2.198964e-04\n",
      "27                           Summary_Light Rain -6.003435e-03\n",
      "15                  Summary_Breezy and Overcast -8.301299e-03\n",
      "31                                 Summary_Rain -1.488916e-02\n",
      "8                                           Day -1.621934e-02\n",
      "5                          Pressure (millibars) -2.150068e-02\n",
      "38                              PrecipType_rain -4.045341e-02\n",
      "3                        Wind Bearing (degrees) -4.156846e-02\n",
      "19                              Summary_Drizzle -9.718482e-02\n",
      "23                                Summary_Foggy -1.496403e-01\n",
      "1                                      Humidity -2.648194e-01\n",
      "32                                Summary_Windy -4.479120e-01\n",
      "16             Summary_Breezy and Partly Cloudy -7.268874e-01\n",
      "14             Summary_Breezy and Mostly Cloudy -9.008289e-01\n",
      "34                      Summary_Windy and Foggy -1.140356e+00\n",
      "18  Summary_Dangerously Windy and Partly Cloudy -1.172376e+00\n",
      "37              Summary_Windy and Partly Cloudy -1.281329e+00\n",
      "35              Summary_Windy and Mostly Cloudy -1.508724e+00\n"
     ]
    }
   ],
   "source": [
    "# 定义目标变量 y\n",
    "y = data['Temperature (C)']\n",
    "\n",
    "# 删除目标变量，剩下的都是特征\n",
    "X = data.drop('Temperature (C)', axis=1)\n",
    "\n",
    "\n",
    "# 将数据集划分为训练集和测试集，比例为 80%:20%\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.20, random_state=42)\n",
    "\n",
    "# 初始化标准化器\n",
    "scaler = StandardScaler()\n",
    "\n",
    "# 识别需要缩放的数值型特征（排除独热编码的特征）\n",
    "numeric_features = ['Apparent Temperature (C)', 'Humidity', 'Wind Speed (km/h)',\n",
    "                    'Wind Bearing (degrees)', 'Visibility (km)', 'Pressure (millibars)',\n",
    "                    'Year', 'Month', 'Day', 'Hour', 'Weekday']\n",
    "\n",
    "# 对训练集进行拟合和转换\n",
    "X_train[numeric_features] = scaler.fit_transform(X_train[numeric_features])\n",
    "\n",
    "# 对测试集进行转换\n",
    "X_test[numeric_features] = scaler.transform(X_test[numeric_features])\n",
    "\n",
    "# 初始化线性回归模型\n",
    "lr_model = LinearRegression()\n",
    "\n",
    "# 训练模型\n",
    "lr_model.fit(X_train, y_train)\n",
    "\n",
    "# 对测试集进行预测\n",
    "y_pred_lr = lr_model.predict(X_test)\n",
    "\n",
    "# 定义评估函数\n",
    "def evaluate_model(y_true, y_pred, model_name):\n",
    "    mse = mean_squared_error(y_true, y_pred)\n",
    "    rmse = np.sqrt(mse)\n",
    "    mae = mean_absolute_error(y_true, y_pred)\n",
    "    r2 = r2_score(y_true, y_pred)\n",
    "    print(f'{model_name} 模型评估结果：')\n",
    "    print(f'MSE: {mse:.4f}')\n",
    "    print(f'RMSE: {rmse:.4f}')\n",
    "    print(f'MAE: {mae:.4f}')\n",
    "    print(f'R² Score: {r2:.4f}\\n')\n",
    "\n",
    "# 评估线性回归模型\n",
    "evaluate_model(y_test, y_pred_lr, '线性回归')\n",
    "\n",
    "\n",
    "# 获取特征名称\n",
    "feature_names = X_train.columns\n",
    "\n",
    "# 获取模型系数\n",
    "coefficients = lr_model.coef_\n",
    "\n",
    "# 创建系数数据框\n",
    "coeff_df = pd.DataFrame({'Feature': feature_names, 'Coefficient': coefficients})\n",
    "\n",
    "# 按系数大小排序\n",
    "coeff_df = coeff_df.sort_values(by='Coefficient', ascending=False)\n",
    "\n",
    "# 输出系数数据框\n",
    "print(coeff_df)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.1 模型性能指标\n",
    "\n",
    "- 均方误差 (MSE): 0.8961\n",
    "- 均方根误差 (RMSE): 0.9466\n",
    "- 平均绝对误差 (MAE): 0.7406\n",
    "- R² Score: 0.9902\n",
    "\n",
    "R² Score (0.9902)：表示模型解释了温度变化的99.02%。这是一个非常高的值，通常表明模型拟合得非常好。然而，过高的R²可能暗示着模型过拟合，尤其是在特征数量较多的情况下。\n",
    "\n",
    "MSE, RMSE, MAE：这些误差指标显示了预测值与真实值之间的差异。较低的值通常表示模型性能良好。\n",
    "\n",
    "### 1.2 模型系数分析\n",
    "\n",
    "以下是部分特征及其对应的回归系数：\n",
    "\n",
    "| Feature                                      | Coefficient    |\n",
    "|-------------------------------------------------|----------------|\n",
    "| Apparent Temperature (C)                        | 9.338752e+00   |\n",
    "| Summary_Breezy and Foggy                        | 1.927948e+00   |\n",
    "| Summary_Dry and Mostly Cloudy                   | 1.083557e+00   |\n",
    "| ...                                             | ...            |\n",
    "| Summary_Windy and Foggy                         | -1.140356e+00  |\n",
    "| Summary_Dangerously Windy and Partly Cloudy      | -1.172376e+00  |\n",
    "| Summary_Windy and Partly Cloudy                  | -1.281329e+00  |\n",
    "| Summary_Windy and Mostly Cloudy                   | -1.508724e+00  |\n",
    "\n",
    "\n",
    "#### 正向影响较大的特征：\n",
    "\n",
    "- **Apparent Temperature (C)**: 回归系数为9.34，表明体感温度对实际温度有显著的正向影响。这是合理的，因为体感温度通常与实际温度密切相关。\n",
    "- **Summary_Breezy and Foggy**、**Summary_Dry and Mostly Cloudy** 等天气描述特征也对温度有正向影响。\n",
    "\n",
    "#### 负向影响较大的特征：\n",
    "\n",
    "- **Summary_Windy and Foggy**、**Summary_Dangerously Windy and Partly Cloudy** 等天气描述特征对温度有显著的负向影响。这可能表明在这些特定天气条件下，温度较低。\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. 随机森林回归模型\n",
    "\n",
    "为了全面评估模型性能，可以继续训练和评估随机森林回归模型。随机森林能够捕捉特征之间的非线性关系，并提供特征重要性分析。\n",
    "\n",
    "### 2.1 模型训练"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "随机森林回归 模型评估结果：\n",
      "MSE: 0.0024\n",
      "RMSE: 0.0494\n",
      "MAE: 0.0136\n",
      "R² Score: 1.0000\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\18154\\AppData\\Local\\Temp\\ipykernel_24540\\1730992633.py:47: UserWarning: Glyph 29305 (\\N{CJK UNIFIED IDEOGRAPH-7279}) missing from current font.\n",
      "  plt.tight_layout()\n",
      "C:\\Users\\18154\\AppData\\Local\\Temp\\ipykernel_24540\\1730992633.py:47: UserWarning: Glyph 24449 (\\N{CJK UNIFIED IDEOGRAPH-5F81}) missing from current font.\n",
      "  plt.tight_layout()\n",
      "C:\\Users\\18154\\AppData\\Local\\Temp\\ipykernel_24540\\1730992633.py:47: UserWarning: Glyph 37325 (\\N{CJK UNIFIED IDEOGRAPH-91CD}) missing from current font.\n",
      "  plt.tight_layout()\n",
      "C:\\Users\\18154\\AppData\\Local\\Temp\\ipykernel_24540\\1730992633.py:47: UserWarning: Glyph 35201 (\\N{CJK UNIFIED IDEOGRAPH-8981}) missing from current font.\n",
      "  plt.tight_layout()\n",
      "C:\\Users\\18154\\AppData\\Local\\Temp\\ipykernel_24540\\1730992633.py:47: UserWarning: Glyph 24615 (\\N{CJK UNIFIED IDEOGRAPH-6027}) missing from current font.\n",
      "  plt.tight_layout()\n",
      "C:\\Users\\18154\\AppData\\Local\\Temp\\ipykernel_24540\\1730992633.py:47: UserWarning: Glyph 65288 (\\N{FULLWIDTH LEFT PARENTHESIS}) missing from current font.\n",
      "  plt.tight_layout()\n",
      "C:\\Users\\18154\\AppData\\Local\\Temp\\ipykernel_24540\\1730992633.py:47: UserWarning: Glyph 38543 (\\N{CJK UNIFIED IDEOGRAPH-968F}) missing from current font.\n",
      "  plt.tight_layout()\n",
      "C:\\Users\\18154\\AppData\\Local\\Temp\\ipykernel_24540\\1730992633.py:47: UserWarning: Glyph 26426 (\\N{CJK UNIFIED IDEOGRAPH-673A}) missing from current font.\n",
      "  plt.tight_layout()\n",
      "C:\\Users\\18154\\AppData\\Local\\Temp\\ipykernel_24540\\1730992633.py:47: UserWarning: Glyph 26862 (\\N{CJK UNIFIED IDEOGRAPH-68EE}) missing from current font.\n",
      "  plt.tight_layout()\n",
      "C:\\Users\\18154\\AppData\\Local\\Temp\\ipykernel_24540\\1730992633.py:47: UserWarning: Glyph 26519 (\\N{CJK UNIFIED IDEOGRAPH-6797}) missing from current font.\n",
      "  plt.tight_layout()\n",
      "C:\\Users\\18154\\AppData\\Local\\Temp\\ipykernel_24540\\1730992633.py:47: UserWarning: Glyph 65289 (\\N{FULLWIDTH RIGHT PARENTHESIS}) missing from current font.\n",
      "  plt.tight_layout()\n",
      "c:\\ProgramData\\anaconda3\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 29305 (\\N{CJK UNIFIED IDEOGRAPH-7279}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "c:\\ProgramData\\anaconda3\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 24449 (\\N{CJK UNIFIED IDEOGRAPH-5F81}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "c:\\ProgramData\\anaconda3\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 37325 (\\N{CJK UNIFIED IDEOGRAPH-91CD}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "c:\\ProgramData\\anaconda3\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 35201 (\\N{CJK UNIFIED IDEOGRAPH-8981}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "c:\\ProgramData\\anaconda3\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 24615 (\\N{CJK UNIFIED IDEOGRAPH-6027}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "c:\\ProgramData\\anaconda3\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 65288 (\\N{FULLWIDTH LEFT PARENTHESIS}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "c:\\ProgramData\\anaconda3\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 38543 (\\N{CJK UNIFIED IDEOGRAPH-968F}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "c:\\ProgramData\\anaconda3\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 26426 (\\N{CJK UNIFIED IDEOGRAPH-673A}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "c:\\ProgramData\\anaconda3\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 26862 (\\N{CJK UNIFIED IDEOGRAPH-68EE}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "c:\\ProgramData\\anaconda3\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 26519 (\\N{CJK UNIFIED IDEOGRAPH-6797}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "c:\\ProgramData\\anaconda3\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 65289 (\\N{FULLWIDTH RIGHT PARENTHESIS}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 导入必要的库\n",
    "from sklearn.ensemble import RandomForestRegressor\n",
    "\n",
    "\n",
    "# 初始化随机森林回归模型\n",
    "rf_model = RandomForestRegressor(n_estimators=100, random_state=42, n_jobs=-1)\n",
    "\n",
    "# 训练模型\n",
    "rf_model.fit(X_train, y_train)\n",
    "\n",
    "# 对测试集进行预测\n",
    "y_pred_rf = rf_model.predict(X_test)\n",
    "\n",
    "# 评估函数\n",
    "def evaluate_model(y_true, y_pred, model_name):\n",
    "    mse = mean_squared_error(y_true, y_pred)\n",
    "    rmse = np.sqrt(mse)\n",
    "    mae = mean_absolute_error(y_true, y_pred)\n",
    "    r2 = r2_score(y_true, y_pred)\n",
    "    print(f'{model_name} 模型评估结果：')\n",
    "    print(f'MSE: {mse:.4f}')\n",
    "    print(f'RMSE: {rmse:.4f}')\n",
    "    print(f'MAE: {mae:.4f}')\n",
    "    print(f'R² Score: {r2:.4f}\\n')\n",
    "\n",
    "# 评估随机森林模型\n",
    "evaluate_model(y_test, y_pred_rf, '随机森林回归')\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "# 获取特征重要性\n",
    "importances = rf_model.feature_importances_\n",
    "\n",
    "# 创建特征重要性数据框\n",
    "feature_importances = pd.DataFrame({\n",
    "    'Feature': X_train.columns,\n",
    "    'Importance': importances\n",
    "})\n",
    "\n",
    "# 按重要性排序\n",
    "feature_importances = feature_importances.sort_values(by='Importance', ascending=False)\n",
    "\n",
    "# 绘制特征重要性图\n",
    "plt.figure(figsize=(12, 8))\n",
    "sns.barplot(x='Importance', y='Feature', data=feature_importances)\n",
    "plt.title('特征重要性（随机森林）')\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "R²得分为1.0，非常不寻常，通常情况下，这可能是由于数据泄露或模型过拟合等问题引起的。\n",
    "\n",
    "需要注意的是，Apparent Temperature (C)（体感温度）与Temperature (C)通常高度相关，可能导致模型几乎完美地预测。\n",
    "\n",
    "### 2.2 检查特征与目标变量的相关性\n",
    "让我们计算Apparent Temperature (C)与Temperature (C)之间的相关系数："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Temperature 与 Apparent Temperature 的相关系数: 0.9926254234649946\n"
     ]
    }
   ],
   "source": [
    "# 计算相关系数\n",
    "correlation = data['Temperature (C)'].corr(data['Apparent Temperature (C)'])\n",
    "print(f\"Temperature 与 Apparent Temperature 的相关系数: {correlation}\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "相关系数接近于1，说明这两个变量几乎是线性相关的。\n",
    "在这种情况下，模型可以轻松地利用Apparent Temperature (C)来预测Temperature (C)，导致过拟合。\n",
    "由于Apparent Temperature (C)与Temperature (C)高度相关，建议从特征矩阵X中移除该特征。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "特征列表（移除 'Temperature (C)' 和 'Apparent Temperature (C)' 后）：\n",
      "['Humidity', 'Wind Speed (km/h)', 'Wind Bearing (degrees)', 'Visibility (km)', 'Pressure (millibars)', 'Year', 'Month', 'Day', 'Hour', 'Weekday', 'Summary_Breezy', 'Summary_Breezy and Dry', 'Summary_Breezy and Foggy', 'Summary_Breezy and Mostly Cloudy', 'Summary_Breezy and Overcast', 'Summary_Breezy and Partly Cloudy', 'Summary_Clear', 'Summary_Dangerously Windy and Partly Cloudy', 'Summary_Drizzle', 'Summary_Dry', 'Summary_Dry and Mostly Cloudy', 'Summary_Dry and Partly Cloudy', 'Summary_Foggy', 'Summary_Humid and Mostly Cloudy', 'Summary_Humid and Overcast', 'Summary_Humid and Partly Cloudy', 'Summary_Light Rain', 'Summary_Mostly Cloudy', 'Summary_Overcast', 'Summary_Partly Cloudy', 'Summary_Rain', 'Summary_Windy', 'Summary_Windy and Dry', 'Summary_Windy and Foggy', 'Summary_Windy and Mostly Cloudy', 'Summary_Windy and Overcast', 'Summary_Windy and Partly Cloudy', 'PrecipType_rain', 'PrecipType_snow']\n"
     ]
    }
   ],
   "source": [
    "# 6. 定义特征矩阵 X，移除 'Temperature (C)' 和 'Apparent Temperature (C)'\n",
    "X = data.drop(['Temperature (C)', 'Apparent Temperature (C)'], axis=1)\n",
    "\n",
    "# 确认特征移除是否成功\n",
    "print(\"\\n特征列表（移除 'Temperature (C)' 和 'Apparent Temperature (C)' 后）：\")\n",
    "print(X.columns.tolist())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "随机森林回归（移除高相关特征后） 模型评估结果：\n",
      "MSE: 2.6677\n",
      "RMSE: 1.6333\n",
      "MAE: 1.1897\n",
      "R² Score: 0.9707\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "# 可视化库\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "# 机器学习库\n",
    "from sklearn.model_selection import train_test_split, GridSearchCV, cross_val_score\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.ensemble import RandomForestRegressor\n",
    "from sklearn.metrics import mean_squared_error, mean_absolute_error, r2_score\n",
    "\n",
    "# 5. 定义目标变量 y\n",
    "y = data['Temperature (C)']\n",
    "\n",
    "\n",
    "# 7. 数据集划分\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.20, random_state=42)\n",
    "\n",
    "# 8. 特征缩放\n",
    "scaler = StandardScaler()\n",
    "numeric_features = ['Humidity', 'Wind Speed (km/h)',\n",
    "                    'Wind Bearing (degrees)', 'Visibility (km)', 'Pressure (millibars)',\n",
    "                    'Year', 'Month', 'Day', 'Hour', 'Weekday']\n",
    "\n",
    "# 仅对数值型特征进行缩放\n",
    "X_train[numeric_features] = scaler.fit_transform(X_train[numeric_features])\n",
    "X_test[numeric_features] = scaler.transform(X_test[numeric_features])\n",
    "\n",
    "# 9. 训练随机森林回归模型\n",
    "rf_model = RandomForestRegressor(n_estimators=100, random_state=42, n_jobs=-1)\n",
    "rf_model.fit(X_train, y_train)\n",
    "\n",
    "# 10. 对测试集进行预测\n",
    "y_pred_rf = rf_model.predict(X_test)\n",
    "\n",
    "# 11. 评估函数\n",
    "def evaluate_model(y_true, y_pred, model_name):\n",
    "    mse = mean_squared_error(y_true, y_pred)\n",
    "    rmse = np.sqrt(mse)\n",
    "    mae = mean_absolute_error(y_true, y_pred)\n",
    "    r2 = r2_score(y_true, y_pred)\n",
    "    print(f'{model_name} 模型评估结果：')\n",
    "    print(f'MSE: {mse:.4f}')\n",
    "    print(f'RMSE: {rmse:.4f}')\n",
    "    print(f'MAE: {mae:.4f}')\n",
    "    print(f'R² Score: {r2:.4f}\\n')\n",
    "\n",
    "# 12. 评估随机森林模型\n",
    "evaluate_model(y_test, y_pred_rf, '随机森林回归（移除高相关特征后）')\n",
    "\n",
    "# 13. 特征重要性分析\n",
    "importances = rf_model.feature_importances_\n",
    "feature_importances = pd.DataFrame({\n",
    "    'Feature': X_train.columns,\n",
    "    'Importance': importances\n",
    "}).sort_values(by='Importance', ascending=False)\n",
    "\n",
    "# 绘制特征重要性图\n",
    "plt.figure(figsize=(12, 8))\n",
    "sns.barplot(x='Importance', y='Feature', data=feature_importances)\n",
    "plt.title('Feature Importance (Random Forest)')\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "随机森林回归模型在移除高度相关特征（Apparent Temperature (C)）后，仍然显示出非常高的性能（R² Score: 0.9707）。\n",
    "\n",
    "后续还需要通过交叉验证的方式来增强模型的泛化能力\n",
    "\n",
    "### 2.3 使用交叉验证\n",
    "\n",
    "使用交叉验证评估模型的性能，以确保模型的稳定性和泛化能力。\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "交叉验证 R² scores: [0.86640369 0.88049583 0.89717949 0.8592042  0.86954611]\n",
      "平均 R²: 0.8746\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import cross_val_score\n",
    "\n",
    "scores = cross_val_score(rf_model, X, y, cv=5, scoring=\"r2\")\n",
    "print(f\"交叉验证 R² scores: {scores}\")\n",
    "print(f\"平均 R²: {scores.mean():.4f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "随机森林回归模型在移除高度相关特征（Apparent Temperature (C)）后，仍然显示出非常高的性能（R² Score: 0.9707）。\n",
    "\n",
    "在移除高度相关特征（Apparent Temperature (C)）后，再使用之前的线性回归模型进行对比。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "线性回归 （移除Apparent Temperature (C)之后）模型评估结果：\n",
      "MSE: 34.3205\n",
      "RMSE: 5.8584\n",
      "MAE: 4.7881\n",
      "R² Score: 0.6231\n",
      "\n",
      "                                        Feature   Coefficient\n",
      "33                      Summary_Windy and Foggy  1.171861e+01\n",
      "24                   Summary_Humid and Overcast  9.566806e+00\n",
      "23              Summary_Humid and Mostly Cloudy  9.091295e+00\n",
      "25              Summary_Humid and Partly Cloudy  8.648518e+00\n",
      "37                              PrecipType_rain  6.050162e+00\n",
      "12                     Summary_Breezy and Foggy  4.073170e+00\n",
      "19                                  Summary_Dry  1.267394e+00\n",
      "6                                         Month  1.069161e+00\n",
      "3                               Visibility (km)  7.485661e-01\n",
      "2                        Wind Bearing (degrees)  2.403551e-01\n",
      "5                                          Year  1.110303e-01\n",
      "7                                           Day  6.250611e-02\n",
      "9                                       Weekday  6.511816e-04\n",
      "11                       Summary_Breezy and Dry  7.127632e-14\n",
      "32                        Summary_Windy and Dry -1.110223e-16\n",
      "8                                          Hour -8.666749e-02\n",
      "4                          Pressure (millibars) -1.307765e-01\n",
      "34              Summary_Windy and Mostly Cloudy -2.536334e-01\n",
      "30                                 Summary_Rain -6.527513e-01\n",
      "26                           Summary_Light Rain -8.239172e-01\n",
      "20                Summary_Dry and Mostly Cloudy -1.130337e+00\n",
      "35                   Summary_Windy and Overcast -1.139040e+00\n",
      "1                             Wind Speed (km/h) -1.307247e+00\n",
      "29                        Summary_Partly Cloudy -1.496011e+00\n",
      "17  Summary_Dangerously Windy and Partly Cloudy -1.623914e+00\n",
      "18                              Summary_Drizzle -1.841583e+00\n",
      "21                Summary_Dry and Partly Cloudy -1.987918e+00\n",
      "13             Summary_Breezy and Mostly Cloudy -2.085075e+00\n",
      "14                  Summary_Breezy and Overcast -2.139956e+00\n",
      "27                        Summary_Mostly Cloudy -2.399273e+00\n",
      "22                                Summary_Foggy -2.623335e+00\n",
      "28                             Summary_Overcast -2.842049e+00\n",
      "16                                Summary_Clear -2.967891e+00\n",
      "15             Summary_Breezy and Partly Cloudy -3.477436e+00\n",
      "10                               Summary_Breezy -3.488622e+00\n",
      "36              Summary_Windy and Partly Cloudy -3.867549e+00\n",
      "0                                      Humidity -5.082043e+00\n",
      "38                              PrecipType_snow -6.050162e+00\n",
      "31                                Summary_Windy -7.525500e+00\n"
     ]
    }
   ],
   "source": [
    "\n",
    "# 对训练集进行拟合和转换\n",
    "X_train[numeric_features] = scaler.fit_transform(X_train[numeric_features])\n",
    "\n",
    "# 对测试集进行转换\n",
    "X_test[numeric_features] = scaler.transform(X_test[numeric_features])\n",
    "\n",
    "# 初始化线性回归模型\n",
    "lr_model = LinearRegression()\n",
    "\n",
    "# 训练模型\n",
    "lr_model.fit(X_train, y_train)\n",
    "\n",
    "# 对测试集进行预测\n",
    "y_pred_lr = lr_model.predict(X_test)\n",
    "\n",
    "# 定义评估函数\n",
    "def evaluate_model(y_true, y_pred, model_name):\n",
    "    mse = mean_squared_error(y_true, y_pred)\n",
    "    rmse = np.sqrt(mse)\n",
    "    mae = mean_absolute_error(y_true, y_pred)\n",
    "    r2 = r2_score(y_true, y_pred)\n",
    "    print(f'{model_name} （移除Apparent Temperature (C)之后）模型评估结果：')\n",
    "    print(f'MSE: {mse:.4f}')\n",
    "    print(f'RMSE: {rmse:.4f}')\n",
    "    print(f'MAE: {mae:.4f}')\n",
    "    print(f'R² Score: {r2:.4f}\\n')\n",
    "\n",
    "# 评估线性回归模型\n",
    "evaluate_model(y_test, y_pred_lr, '线性回归')\n",
    "\n",
    "\n",
    "# 获取特征名称\n",
    "feature_names = X_train.columns\n",
    "\n",
    "# 获取模型系数\n",
    "coefficients = lr_model.coef_\n",
    "\n",
    "# 创建系数数据框\n",
    "coeff_df = pd.DataFrame({'Feature': feature_names, 'Coefficient': coefficients})\n",
    "\n",
    "# 按系数大小排序\n",
    "coeff_df = coeff_df.sort_values(by='Coefficient', ascending=False)\n",
    "\n",
    "# 输出系数数据框\n",
    "print(coeff_df)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "将四种模型对比在一起看。形成如下图表"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                                        MSE    RMSE     MAE  \\\n",
      "Model Name                                                                    \n",
      "Linear Regression (Remove Apparent Temperature ...  34.3205  5.8584  4.7881   \n",
      "Random Forest Regression (Remove Highly Correla...   2.6677  1.6333  1.1897   \n",
      "Random Forest Regression (Include Apparent Temp...   0.0024  0.0494  0.0136   \n",
      "Linear Regression (Include Apparent Temperature...   0.8961  0.9466  0.7406   \n",
      "\n",
      "                                                    R² Score  \n",
      "Model Name                                                    \n",
      "Linear Regression (Remove Apparent Temperature ...    0.6231  \n",
      "Random Forest Regression (Remove Highly Correla...    0.9707  \n",
      "Random Forest Regression (Include Apparent Temp...    1.0000  \n",
      "Linear Regression (Include Apparent Temperature...    0.9902  \n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABuMAAAVnCAYAAABIIhBmAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8fJSN1AAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOzdd3zN9/v/8ec5GST2SGKWiL1jlBqltNRoSSmtGTVqFaXlY1OztYoi1Kyidqla0daoKqJWiRFNYlSEUBIJWef3h1/OVypRkpyck3jcb7feKu/xOtc53k7Oda7X+3oZTCaTSQAAAAAAAAAAAADSnNHaAQAAAAAAAAAAAACZFcU4AAAAAAAAAAAAwEIoxgEAAAAAAAAAAAAWQjEOAAAAAAAAAAAAsBCKcQAAAAAAAAAAAICFUIwDAAAAAAAAAAAALIRiHAAAAAAAAAAAAGAhFOMAAAAAAAAAAAAAC6EYBwAAAAAAAAAAAFiIvbUDAIDM7urVq2rcuLH5586dO2vUqFH/ed6SJUv0xRdfSJLc3Ny0f//+JI/75ZdftG3bNp04cUK3bt2S0WhUvnz5VKVKFTVt2lRNmjRJ8ry5c+fqq6++eq7nMnz4cHl7ez/XOZIUFxenPXv2aMeOHTp16pRu3rwpg8EgV1dXeXp6qm3btqpVq9Zzj/sie/y62r17t4oVK2bliAAAAIDMpUyZMk/db29vr2zZsqlIkSKqX7++unfvrpw5cz51nNdee00+Pj7/+dg7d+7UwIEDzT+fOXNG9vZPfo3n5+en77//XkePHlVoaKhMJpPy5s2r8uXLq3HjxnrrrbeSPG/Tpk0aPnz4f8bxuC5dumjkyJHPdU6CX3/9Vdu2bdPx48cVEhKiuLg45c+fX5UrV9bbb7+t119/PUXjvsgSrqtly5apTp06Vo4GAPBfKMYBQDrbtWuXRo4cKYPB8NTjtm/f/tT9Dx8+1EcffaR9+/ZJklxcXFSyZElJjwo127Zt07Zt21S9enUtWLBAuXLlSnIcR0dHVaxY8Zlid3Nze6bjHvfXX3/p448/1rlz5yRJzs7OKl68uGJjY3X16lVt3bpVW7du1ZtvvqkpU6bI2dn5uR8DAAAAACylePHiyps37xPbo6OjdeXKFZ05c0ZnzpzRpk2btG7dOhUsWDDZsQ4ePKiIiAhlz579qY/5X/lgfHy8Ro8erQ0bNkiScufOLXd3d9nZ2en69evy9fWVr6+vFi9erIULF6pIkSLJjlWtWrWnPlaCokWLPtNxjwsNDdWnn36q33//XZKUJUsWFSpUSA4ODrp69ap27dqlXbt26eWXX9aXX36pfPnyPfdjAACQEVCMA4B0ZG9vr9DQUB07dkw1atRI9rgrV67ozz//fOpYY8aM0b59+1SiRAl98cUXqlSpknmfyWTSr7/+qv/97386duyY+vXrp2+//TbJcVxcXLRmzZqUPaH/cPToUfXq1UuRkZGqWLGiBgwYoAYNGpj3P3jwQN99951mz56tnTt36s6dO1q6dGmSMzeRmJubmzlBL1SokJWjAQAAADKvDz/8UO+8806S++Lj4/XDDz9o5MiRCg0N1fDhw7V8+fIkj7W3t1d0dLR++ukntWrVKtnHi4yMNE+6TM5XX32lDRs2yMXFRdOmTVPt2rUTTfg8ceKEhg0bpoCAAHXv3l0//PCDHB0dkxzLUvngpUuX1KlTJ92+fVvFixfXgAED9Oabb8rOzk6SFBsbqy1btmjGjBk6cuSIunbtqu++++4/C5V4hHwQADIW1owDgHRUu3ZtSY9ajjxNwofq8uXLJ7n/2rVr2rp1q6RHSdjjhThJMhgMql+/vmbNmiXpUVHs0KFDqYr9ed25c0dDhgxRZGSk6tWrp9WrVycqxElS1qxZ5e3trXnz5slgMOjw4cPJFg2RmIODgzw8POTh4SEHBwdrhwMAAAC8kIxGo1q1aqWePXtKkg4dOqTAwMAkj33WfPDnn3/WgwcPks0Ho6KizAW/yZMn65VXXnmi80rVqlW1YMECZcmSRUFBQdqyZcvzPK1Ui46O1uDBg3X79m2VL19ea9euVYsWLcyFOOlRcbJNmzZavny5smbNqosXL+rLL79M1zgzsoR80MnJydqhAACeAcU4AEhHb775pqRHa3yZTKZkj9u+fbuMRqOaNWuW5P6zZ88qPj5e2bNnl4eHR7LjvPzyyypevLgk6eTJkykPPAW+/PJL3bhxQ87Ozpo2bZqyZMmS7LF16tQxP9dly5YpPj4+vcIEAAAAgFR77bXXzH8OCAhI8piEfPDXX39VREREsmMlTM5s3rx5kvsDAwN1//59SVKVKlWSHadEiRKqWbOmJOnUqVNPiT7tLV++XOfOnZPRaNS0adOUO3fuZI8tXbq0OnfuLElav379U18bAAAyKvqAAUA6qlGjhlxcXHTjxg398ccfql69+hPH/PXXXzp37pxq166t/PnzJzlOwp1QERER8vPze2rLy0WLFslkMsnFxSVtnsQzePjwofnOvbZt2ya5vsK/9evXT2+++aaqV68uozHxXJG4uDht2rRJW7du1blz5xQVFaX8+fOrZs2a8vb2VoUKFRIdf/XqVTVu3Fhubm7au3ev1qxZo/Xr1yswMFBOTk6qXr26Bg8eLA8PD92+fVvz5s3TTz/9pFu3bilfvnxq3LixPv74Y+XIkcM85uHDh9WlSxeVLVtW69ev1/z58/XDDz8oNDRULi4uqlOnjnr27KlixYol+fyOHDmi9evX6/jx47p165ZiY2OVJ08eVa1aVR06dNArr7yS6Pi5c+fqq6++Us+ePVW1alVNmzZN165dk6urq4YMGaIqVaqocePGkh4Vdx9/3EuXLmnx4sU6deqUrl27Jjs7OxUtWlQNGjRQly5dklyHIaWvcf78+fXrr79qw4YNWrdunfmLh9KlS6tdu3Z65513/nN9RAAAACCjezyHSW7iZeHChVW5cmWdOnVKP//8s95+++0njomIiNCBAwdUtGhRVa5cOclxHu+M8csvv6h169bJxvXZZ5/pwYMHcnV1fcZnkjbWr18v6VGRMmFt86fp3LmzSpcurerVqyfZpnLXrl1av369/vzzT0VERCh37tzy9PRMMpeSpDJlykiSzpw5o127dmnlypU6f/687O3tValSJX300Ufy9PRUZGSkFi5cqO3bt+v69evKmTOn6tWrpyFDhiRaMz0h/8mRI4eOHDmib775RmvXrtW1a9eUJ08eVatWTT179kz2bkZ/f3+tXr1afn5+unHjhqKjo5UzZ05VqFBBbdq0MRdqE2zatEnDhw9X8+bN1alTJ3322We6dOmScufOrR49esjb29v8HJctW6Y6deqYz71x44a+/vprHTlyRFevXpXJZFLBggVVp04deXt7J7t+YEpf41OnTmn//v365ptv5O/vr5iYGLm7u6t169bq2LEjnVwA4P/jzjgASEdGo1FNmzaVlHxrkoRZkC1atEh2nGrVqsnZ2VmS1KtXL82aNSvZ2ZfFihVT8eLFlS1bttSE/lyOHz+uyMhISVLdunWf6ZySJUuqadOmTxQgIyIi1LFjR40aNUpHjhxRjhw5VKZMGYWHh2vr1q1q27atli1bluSY8fHxGjhwoD777DPdvn1bxYoVU0REhPbs2aP3339fx48fV+vWrbV69WplzZpVhQoVUkhIiFatWqWePXsmmUTHxsaqV69eWrBggR4+fKhSpUopLCxM69ev1zvvvGNemPxxM2bMUOfOnbV161bdv39fJUqUUKFChXT79m3t3r1b3t7eWrt2bZLP4ejRoxowYIDu3bsnDw8PhYaGqly5csm+jsePH1fbtm21adMmhYaGyt3dXW5ubrpw4YJ8fHzk5eWl69evp9lrbDKZNGzYMI0aNUpBQUFyd3eXvb29Tpw4oREjRmjGjBnJxgoAAABkFgl5nNFoTLaIJsncESS5fHDPnj2Kjo5+aj5YokQJFS5cWJI0atQoTZw4UadPn04yfylcuLA8PDwSTTS0tCtXrujy5cuSnj0fdHNz09tvv21+XgliYmLUv39/DRgwQAcOHJC9vb3Kli2r2NhYcy41efLkZMedMmWKBg8erODgYBUrVkzR0dE6ePCgunTpot9//13t2rXTwoULFR8fr+LFiyssLExbtmxRp06dFBUVleSYw4cP15QpU3T79m2VKlVK9+/f1/bt29WuXTtt27btieNXr16td955R+vWrVNYWJiKFSumokWLKjw8XPv379fAgQPNS0z8219//aUePXro2rVrKlWqlO7du/fU4ubly5fl5eWllStX6sqVKypcuLCKFCmiK1euaOXKlWrVqpXOnj2bpq/xl19+qf79++vPP/9UkSJFlC1bNvn7+2vKlCkaOnRosucBwIuGYhwApLOE5Cu5VpU7duyQg4ODmjRpkuwYOXPm1PDhwyVJ9+/fl4+Pj1q0aKFXX31VQ4YM0Zo1axQUFGSR+J/FX3/9Zf5z2bJlUzXWJ598ouPHj8vFxUXffPONfv75Z23cuFGHDh1S3759FR8fr6lTp2r37t1PnHvz5k39/PPPmjp1qvbt26etW7dq06ZNcnJy0t27d9WhQwfly5dPO3bs0M6dO7V7925zknH8+HEdPXr0iTEDAgL0+++/a/jw4dq/f782bdqk/fv3q3HjxoqIiNDgwYMVHh5uPv7w4cNatGiRjEajJk+erIMHD2rTpk3avXu3fvrpJ7388suSpDlz5iTZnvPEiRNq1KiR9u3bpy1btmj//v0qUaJEsq/XlClTFBkZqc6dO+vgwYPavHmztm/frl27dql48eK6ceOGFixYkGavcVhYmLZt26aRI0fq999/16ZNm/Trr7+aZ/kuW7ZMt2/fTjZeAAAAICOLjo7WN998Y17DrU2bNipQoECyxzdr1kwGgyHZVpU//vijpORbVEqSnZ2dxo0bJ3t7e8XExGjlypVq27atXnnlFX300UfmFpHW8ng+mHD3VEpNnTpVvr6+cnZ21uzZs81dOQ4ePKgxY8bI3t5eK1asML/+//btt99qyJAhOnDggL7//nvt2rVLrq6uio6OVrdu3RQVFaV169bpp59+0rZt27R06VLZ2dnp8uXLSRZMw8PD9f333+uDDz7QgQMHtHHjRv36669q3769YmJiNGLECF25csV8fFBQkCZPnqz4+HgNGjTInKPt2LFDBw4cMH8/sGTJEt29e/eJxzt37pxKly6tX375RZs3b9a+ffueWuCcNWuWwsLC1LRpU/3666/64Ycf9MMPP+iXX36Rp6enIiIinpgwmdrXeOnSpfrwww/1+++/6/vvv9eBAwfUq1cvSY+K1P7+/snGCwAvEopxAJDOqlevLjc3N4WEhOj48eOJ9p0/f14BAQGqU6fOU3vqS1K7du20YMGCRDMHb9y4oW3btmncuHFq2rSpmjdvrk2bNj11fbpr166pTJky//lfQg//Z/F4EvEsLSqTc+LECf3yyy+SHhWratWqZd7n6OiogQMHqn379pKk6dOnJzlG27Zt5eXlZW6VWLp0aXN7R5PJpNmzZ5vX1ZMeJc8Jr+m/Zwwm6Natm7y9vc2taHLlyqVZs2apSJEiCgsL05o1a8zHHjhwQI6OjnrjjTfUpk2bRO1rChQooIEDB0qSbt26pbCwsCQfb9iwYXJ0dJT0369nQtLdpk0b8zmSVLRoUQ0bNkyvvfZaomsmLV7jDh06qEuXLubF2LNkyaIRI0bIYDAoNjY23denAAAAANLSwoUL9f777yf677333lPLli1VvXp1TZo0SXFxcWrevLlGjRr11LEKFiyoKlWq6OHDh+bP4Qn++ecfHTp0SCVLlvzPItarr76qlStXqnTp0uZtd+7c0e7duzVlyhS1atVKjRo10rJlyxQbG/vUsZ4lH2zUqNF/vEr/J63ywZCQEH333XeSpAkTJiRq5WhnZ6eOHTua86mvvvrKvI7e4+rXr69evXrJ3v7RSj0FChSQl5eXpEedVCZNmpToTsa6deual5M4c+ZMknE1bdo0UY6WNWtWjR8/Xp6ennr48KG+/vpr87EHDx6UnZ2dKlSooD59+iRq2Zg7d24NGzZM0qO70wIDA5N8vEGDBpnvbMyTJ89TlwFIyAfffvvtRN1x8ufPr5EjR6p+/fqJ7qxLi9f4tdde0+DBg83rxNvZ2WnQoEHKlSuXJOmPP/5INl4AeJFQjAOAdGYwGJJtVflfC3X/W6NGjeTr66ulS5eqc+fOT7SruHTpkoYPH64+ffooOjo6yTEcHR1VrVq1//zv8STvvzg5OZn/HBMT88zn/VtCclq5cmVVq1YtyWM++OADSVJwcLAuXLjwxP6GDRs+sS2hGOXu7q6XXnrpif0J6ykkt3B4165dn9iWJUsWc1L3008/mbd/8sknOnXqlKZNm5bkWFmzZjX/+cGDB0/sd3FxUdGiRZM8NykJa8eNHTtWhw4dSvT6N2rUSD4+Pvrwww/N29LiNX58sfoEefLkMSfe9+7de+b4AQAAAFsTFBSkP/74I9F/x48f18WLF1WoUCF17txZ3333nWbNmpXo831ykmtV6evrq5iYmGfOB6tVq6atW7dqzZo16t69uypUqJBo8t+1a9c0depUvffee4m6dyQ1zn/9V7FixWeKSZJ5SQVJ/1kIfJr9+/crNjZWLi4uyb4mnTp1koODg8LDw3XkyJEn9j8tH3RycjJ3KnlcQj6YVOFJSjofNBgMeu+99yRJP//8s3l7x44ddfLkSa1evTrJsR6/XpJqi2k0GuXp6ZnkuUlJyAenT5+uPXv2JMoxK1WqpMWLF5u77Ehp8xonVai1s7Mzx0I+CACP2Fs7AAB4ETVr1kzffPONdu3apeHDh5tntu3cuVNZsmTR66+//sxj2dnZqW7duuZWFbdv39bhw4e1d+9ebd++XdHR0frll180d+5cDRky5InzXVxcEt3JlRYeXxz8zp07KV6vLqG9SYUKFZI9pnjx4sqePbsiIiIUGBj4RNGwYMGCT5yTMBsxuVmaCfuTuqPQ1dU12bYzCS05/90i1GAwyGg0ys/PTwEBAeY1FM6fP6/g4GDzcUm1qXzehdY//fRT9enTRydPnpS3t7ecnZ1Vs2ZN1alTRw0bNkx0F6CUNq/x4wubPy4hsYyLi3uu5wAAAADYkilTpuidd96R9Ogz+7Vr17R48WJ99913Cg0NVfHixZ+rYNKsWTNNnTpVBw4cUEREhLJnzy7p2dYP/zeDwWAumEmP2igePXpU+/fv1w8//KCIiAidPn1aY8eO1cyZM5McI63zQRcXF/Of79y5k+JxEnKVcuXKJSoyPs7Z2Vnu7u66cOGCAgMDn5gomFTulpDv5c6dO8lxn5YPGgwGVapUKclYEu5mvHnzZqK/V+nR5M1Tp07pwoUL5nzwwoULiVp6JvV4OXPmfKYCb4KBAwfq8OHDCgwMVL9+/eTo6ChPT0/VrVtXDRo0eGIZibR4jckHAeDZcGccAFiBp6enChYsqJCQEJ04cULSoxYYQUFBatiwYaIP7c8rb968atasmT7//HPt3r3bXDhZvXr1U9tVpiV3d3fzny9evPhM58THx8vf3z9RQSrhzrT/Wmw8odiX1MzFx+/S+7fkko2neVr70IQZoI/POjWZTFq+fLkaNWqkjh07auzYsVq8eLF8fX1lZ2enVq1aPfXxElp9PKtXX31VGzZsUIsWLZQtWzZFRkZq3759mjJlipo2baoOHTooICDAfHxavMaPt1pJSnpddwAAAIClGY1GFS1aVOPHj1f//v0VGRmpCRMmaMmSJc88hpubm7ml4d69eyX936TKChUqPDGB7nnkyJFDjRo10rhx4/Tzzz+b7/zasWNHuq3l/NJLL5lb2D9rPihJ/v7+ie6ke9ZcJSF/TipXefwuvX9LST7o5OSUaDmA5B7r8Zxwy5YtevPNN/Xuu+9q5MiR8vHx0fbt2/XgwQO1bdv2qY/3vPlguXLltHXrVr377rvKnTu3oqOjdfjwYc2cOVOtWrXSW2+9JT8/P/PxafEakw8CwLOhGAcAVpBUq8pnbVEZFxend999V6+99poOHz781GMLFixo7kEfERGhmzdvpjb0Z1KuXDlz64+DBw8+0zknT55U69atVbt2bXNv/oQC0NNaqjy+P6V34D2PyMjI/4zj8Tvu5s2bpylTpig0NFTNmzfX1KlTtWHDBh07dkw7duxQ37590zzGcuXKaebMmTp8+LBWrVqlAQMGqEaNGjIajTp27Ji8vb3Nz8MWX2MAAAAgI+jfv7/q1asn6VFbwEOHDj3zuf9uVblz507FxcU9011xvXv3VuPGjfX9998/9bhcuXLps88+k/Ro8uPjXTksKU+ePOY79Z41H7xx44a8vLxUs2ZNc5vHZ81VEtogpkeu8vDhw2SLS4/HmZATbt68WUOHDlVQUJDq16+vzz77TGvWrNGRI0f0008/acyYMWkeY9GiRTVx4kQdOnRI69ev16effqp69erJwcFBFy5cUI8ePXT9+nVJtvkaA0BmRTEOAKwkIfnatWuXTCaTduzYIWdn5yR72j/Ozs5Ot27d0t9//22eRfk0CS1CjEbjU+/qSmsJRcXNmzcrLCzsP49ftWqVpEdxlipVSpJUokQJSckvnC09WhcvobCU0JPekq5fv57sWnL+/v6SZF67LyYmxjxDtl+/fpo1a5a8vLxUqVIlcxITEhKSZrHFxcUpODhYR48elfRohmKNGjXUr18/rVq1SqtWrZLBYNDNmzf122+/SbLN1xgAAADICAwGgyZPnqwcOXIoPj5ew4YNSzZX+Lc333xTRqNRBw4c0P3797Vjxw4ZDIZnWi8uIiJCV69eTbQ2WXIebxmZXJt+S0goKu7bty/Jdaf/LaGTS0xMjCpXrizp/3KVf3dQeVxERIR5mYD0yFXi4uJ06dKlJPcl5IMvvfSS+Y62hQsXSpJat26txYsXq3379qpWrZpy5colKW3zQZPJpKtXr5oLoEajUZUrV1aPHj20ZMkS/fDDD8qePbuioqK0e/duSbb5GgNAZkUxDgCspGrVqipcuLCuX7+uVatW6dq1a2rcuPEz9YN/++23JUnfffedzp8//9Rjf/zxR0lSnTp1km2nYQkffvihXFxcFBERoZEjR+rhw4fJHrtnzx5t27bNfF5CnAm96E+dOqU//vgjyXOXL18u6dFaAAk9+i0pLi5OmzdvfmJ7VFSUtmzZIulRYi09Wh8hoYiV3Jps69evN/85NYubS49awDRp0kRdu3ZN8i5IT09PcxEwIdGyxdcYAAAAyCjc3NzM3Uhu3LihL7744pnOc3V1VbVq1fTgwQNt3LhRfn5+5uUM/ktCPujr6/ufd+Ml5IMlSpRQ0aJFnym2tPDuu++qdOnSiouL04gRI/TPP/8ke+ypU6e0dOlSSdJ7772n/PnzS3rUgt/e3l43b940d5L5t2+//VaxsbFycnIyt+S0tA0bNjyxLT4+XmvXrpX0f/mgJF29elVS8vng42OlNh/8559/1LRpU33wwQc6ffr0E/vd3d1VqFAhc7yS7b7GAJAZUYwDACtKaFWZsJD2sy7U3a1bNxUvXlyRkZHq3LmzVq5cqbt37yY65vbt25oxY4YWLVqkrFmzavDgwWkb/H/IkSOHJkyYIAcHB/3yyy/q2LGjDhw4kKilR0REhObPn69BgwbJZDKpTp066tKli3m/p6enGjRoIEkaMGBAorac0dHRmjNnjtatWydJGjp0qAwGQ7o8txkzZsjX19f88+3btzVgwAD9/fffcnd3Ny/unjdvXvPdiMuXL0/0d3T79m2NGzfOXISUpAcPHqQqrrJly5oT3sGDByeaZRkdHa1Zs2YpIiJCzs7OqlGjhiTbfY0BAACAjKJt27bmIsW6devMnSr+S0K3lC+//FLx8fHPnA+2bt1anp6eio+PV+/evfXVV189MRkvIiJCS5cu1YQJE2Q0GjVs2LAUrZGWUvb29po0aZJy5Mih06dPq3379uZWnAkePnyo1atXy9vbW9HR0SpdunSivLVgwYJq166dJGn06NHmlp7So2LS6tWrNXfuXElS3759/3Pds7TyzTffaM2aNebc9v79+xo5cqROnz6tPHnyqFu3buZjE+48W7t2rW7cuGHeHhERoblz52rRokXmbanNB/PkyaP69etLkkaMGJHoDr74+HitWrVKFy5ckMFgMB9nq68xAGRG9tYOAABeZM2aNdPSpUt1//595cqVy7zewH/JnTu3li1bpo8//lgnTpzQxIkTNXXqVBUpUkQ5c+bUvXv3FBwcLJPJpHz58mnq1KnJzsS7efOm3n///Wd6XBcXF82ZM+eZn99rr72mJUuWaMCAATp9+rR69OihnDlzqkiRIoqNjVVgYKBiYmIkSS1bttSkSZPMC30n+OKLL9S7d28dP35cXbp0UeHChZU3b14FBgYqIiJCdnZ2GjRo0DMnrmmhaNGi6t+/vwoXLqzcuXPr4sWLio6OVqFChTRnzhzznX329vYaOHCgxo8fryNHjqhBgwYqXry4oqOjFRwcrNjYWJUvX17Xr1/XnTt3FBISkuzf07OaNWuW3nvvPR05ckSvv/66ihQpIicnJ129elX37t2TnZ2dPvvss0QtamzxNQYAAAAyCoPBoPHjx6tVq1aKjo7WqFGj9MMPP/xnZ5KmTZtq0qRJun//vuzs7BLdUfU0jo6OWrRokT755BPt27dPc+fO1VdffaUiRYooT548un//vjnfcHZ21sSJE5+6HMKz5oOStGbNmmc+tnLlylq1apV69+6toKAgDRw4UM7OzipatKiMRqP++usvcweVOnXqaObMmXJ2dk40xvDhw3Xjxg399NNPGjhwoFxdXVWgQAFduXJFd+7ckSR16tRJPXv2fOa4UsvDw0Pjxo3TvHnzVKBAAXNb/9y5c2vOnDmJcq2PP/5Yffv2VUBAgBo3bix3d3dJUnBwsB4+fKiiRYvKYDDo8uXLadKy8rPPPlP79u114cIFtWzZUkWKFFGOHDn0999/m1+vwYMHm5dWkGzzNQaAzIhiHABYUeXKlVWkSBFdvXpVb7zxhhwcHJ753EKFCum7777TTz/9pJ9++kknTpzQ7du3dfXqVeXKlUuenp5q1KiR2rVrZ+5Hn5To6Ohk2xP+W+HChZ85vgS1atXS7t27tWHDBu3bt0+XLl3SxYsXZWdnp0KFCql69epq06aN+U6tf8udO7dWrlypzZs3a+vWrTp//rxu3rwpNzc3vfnmm+rYsaPKly//3HGlxsqVK+Xj46MdO3YoICBAhQsX1ptvvqmuXbsqT548iY7t0KGD3N3d9fXXX+vixYu6ePGismfPripVqqhFixZq166dRo0ape+//16//PKLGjdunKrYSpYsqc2bN2vJkiU6dOiQ/v77b5lMJrm6uuqNN95Qt27dzGvyJbDF1xgAAADISEqUKKHevXtrzpw5CgoK0rx58/Txxx8/9RwXFxfVqFFDR44c0csvv2xuz/gscubMqUWLFun333/Xrl275Ofnp1u3bikkJETZsmVT2bJl1bBhQ7Vr105ubm5PHetZ88GUKFOmjHbs2KHNmzfr559/1rlz5/TXX3/JYDDIxcVFlStXVuvWrZMtFjo6OmrevHnasWOHNm7cqD///FP+/v5ycXFRnTp11L59e9WqVcti8Sdl1qxZ2r17tzZv3qzz58/Lzc1Nbdq0Uffu3Z9oM/raa69pw4YNmj9/vs6ePau//vpLTk5OKl26tJo0aaKOHTtqyZIlmjdvnn755ZdEnWJSwtXVVRs2bNCSJUt04MABXblyRdevX1e+fPnUokULderUSdWqVUt0ji2+xgCQGRlMj/cLAwAASTp8+LA5MTpz5ozs7ZnPAgAAAAAvgqtXr5onTu7evVvFihWzckQAgIyGNeMAAAAAAAAAAAAAC6EYBwAAAAAAAAAAAFgIxTgAAAAAAAAAAADAQijGAQAAAAAAAAAAABZiMJlMJmsHAQAAAAAAAAAAAGRG9tYOwJqOHz8uk8kkBwcHa4cCAAAAIIViYmJkMBjk6elp7VBgI8j1AAAAgIwvM+V6L3QxzmQyiRsDAQAAgIyNz/T4N3I9AAAAIOPLTJ/pX+hiXMIsyUqVKlk5EgAAAAApdfr0aWuHABtDrgcAAABkfJkp1zNaOwAAAAAAAAAAAAAgs6IYBwAAAACwCd9//72aN2+uSpUqqUWLFtqxY4e1QwIAAACAVLOpYlxYWJg+/fRT1a5dW56enurVq5cCAgLM+4cPH64yZcok+u/VV1+1YsQAAAAAgLSwZcsWjRgxQu3bt9e2bdvUvHlzDR48WMePH7d2aAAAAACQKja1ZlyfPn1kNBr19ddfy9nZWbNnz5a3t7d8fX3l5OSk8+fPq3fv3urUqZP5HDs7OytGDAAAAABILZPJpNmzZ6tr167q2rWrJKlfv376448/dOTIEXl6elo5QgAAAABIOZspxt25c0dFihRRnz59VKpUKUlS37591apVK128eFEVKlRQQECA+vbtKxcXFytHCwAAAABIK3/99ZeuXbumt956K9H2JUuWpHhMk8mkyMjI1IYGAAAAwEpMJpMMBoO1w0gTNlOMy5Mnj2bOnGn++datW1qyZIkKFCigkiVLKigoSA8fPpSHh4cVowQAAAAApLWgoCBJUmRkpLp3766zZ8+aJ2s2atQoRWPGxMTI398/DaMEAAAAkN4cHR2tHUKasJli3ONGjx6tdevWydHRUQsWLJCzs7MuXLggg8GgFStWaP/+/TIajWrQoIEGDRqkHDlypPixmC0JAAAAZGyZabbkiyoiIkKSNGzYMPXv31+ffPKJdu3apb59+2rZsmV65ZVXnntMBwcHlSxZMq1DBQAAAJBOAgICrB1CmrHJYlzXrl3Vvn17rVmzRv369dPq1at18eJFGY1GFS5cWD4+PgoODtbnn3+uCxcuaMWKFTIajSl6LGZLAgAAABlfZpkt+aJycHCQJHXv3l1eXl6SpHLlyuns2bMpLsYZDAY5OzunaZwAAAAA0k9mmnRpk8W4hNmLEyZM0IkTJ/Ttt99q8uTJ8vb2Vs6cOSVJpUuXlouLi9q3b6/Tp0+rSpUqKXosZksCAAAAGVtmmi35oipQoICkR3ne40qWLKm9e/daISIAAAAASDs2U4wLCwvToUOH1KxZM9nZ2UmSjEajPDw8FBoaKoPBYC7EJUhI1EJCQlJcjGO2JAAAAJCxZabZki+q8uXLK1u2bDp58qRq1Khh3n7hwgW99NJLVowMAAAAAFIvZb0dLSA0NFRDhgzRkSNHzNtiYmJ09uxZeXh4aMiQIerevXuic06fPi1J3NkGAAAAABlY1qxZ1aNHD82bN0/btm3T5cuXtWDBAh08eFDdunWzdngAAAAAkCo2c2dc2bJlVa9ePY0fP14TJ05Uzpw55ePjo3v37snb21vnz59Xnz59tGDBArVo0UKBgYH67LPP1LJlS3l4eFg7fAAAAABAKvTt21dOTk6aNWuWbty4IQ8PD82dO1e1atWydmgAAAAAkCoGk8lksnYQCcLDwzVjxgzt2bNH4eHhqlGjhv73v/+pVKlSkqRdu3bJx8dHf/31l3LkyKG33npLgwYNUpYsWVL0eAl31lWqVClN4o+PN8lopEUO0h7XFgAAQPLS+nM9Mj5yPWQUXFsAAADJy0y5nk0V49KbJf4i5605qGuhd9NsPKCway71e7+utcMAAACwWZkpQUPaINdDRkCuBwAA8HSZKdezmTaVmcW10LsKunbH2mEAAAAAANIQuR4AAACAlDJaOwAAAAAAAAAAAAAgs6IYBwAAAAAAAAAAAFgIxTgAAAAAAAAAAADAQijGAQAAAAAAAAAAABZCMQ4AAAAAAAAAAACwEIpxAAAAAAAAAAAAgIVQjAMAAAAAAAAAAAAshGIcAAAAAAAAAAAAYCEU4wAAAAAAAAAAAAALoRgHAAAAAAAAAAAAWAjFOAAAAAAAAAAAAMBCKMYBAAAAAAAAAAAAFkIxDgAAAAAAAAAAALAQinEAAAAAAAAAAACAhVCMAwAAAAAAAAAAACyEYhwAAAAAAAAAAABgIRTjAAAAAAAAAAAAAAuhGAcAAAAAAAAAAABYCMU4AAAAAAAAAAAAwEIoxgEAAAAAAAAAAAAWQjEOAAAAAAAAAAAAsBCKcQAAAAAAAAAAAICFUIwDAAAAAAAAAAAALIRiHAAAAAAAAAAAAGAhFOMAAAAAAAAAAAAAC6EYBwAAAAAAAAAAAFgIxTgAAAAAAAAAAADAQmyqGBcWFqZPP/1UtWvXlqenp3r16qWAgADzfn9/f3Xq1ElVq1ZVw4YNtWTJEitGCwAAAAAAAAAAADydTRXj+vTpoytXrujrr7/Whg0blDVrVnl7eysqKkp37txRt27dVLx4cW3cuFEfffSRZs+erY0bN1o7bAAAAAAAAAAAACBJ9tYOIMGdO3dUpEgR9enTR6VKlZIk9e3bV61atdLFixd16NAhOTo6aty4cbK3t5eHh4eCg4P19ddfq02bNlaOHgAAAAAAAAAAAHiSzRTj8uTJo5kzZ5p/vnXrlpYsWaICBQqoZMmSmjt3rmrWrCl7+/8LuXbt2lq4cKHCwsKUL1++FD2uyWRSZGRkquM3GAxycnJK9ThAcqKiomQymawdBgAAgM0xmUwyGAzWDgMAAAAAgCTZTDHucaNHj9a6devk6OioBQsWyNnZWSEhISpdunSi41xdXSVJf//9d4qLcTExMfL39091zE5OTipfvnyqxwGSExgYqKioKGuHAQAAYJMcHR2tHQIAAAAAAEmyyWJc165d1b59e61Zs0b9+vXT6tWr9eDBgycS7CxZskiSHj58mOLHcnBwUMmSJVMVryRm4sLi3N3duTMOAAAgCQEBAdYOAWng2rVratSo0RPbJ06cqHfffdcKEQEAAABA2rDJYlxCcWzChAk6ceKEvv32W2XNmlXR0dGJjksowjk7O6f4sQwGQ6rOB9ILbVABAACSxsS4zOH8+fPKkiWL9uzZk+jvNEeOHFaMCgAAAABSz2aKcWFhYTp06JCaNWsmOzs7SZLRaJSHh4dCQ0NVoEABhYaGJjon4Wc3N7d0jxcAAAAAkHYuXLggd3d383IEAAAAAJBZGK0dQILQ0FANGTJER44cMW+LiYnR2bNn5eHhoZo1a+rYsWOKi4sz7z906JDc3d1TvF4cAAAAAMA2nD9/Pk2WEAAAAAAAW2Mzd8aVLVtW9erV0/jx4zVx4kTlzJlTPj4+unfvnry9vZUlSxYtXrxYI0eOVI8ePXTq1CmtWLFC48ePt3boAAAAAIBUunDhglxcXNShQwcFBQWpWLFi6tu3r+rXr5+i8UwmkyIjI1Mdl8FgoGU8LCoqKor1wQEAAJJgMpkyzbIENlOMMxgM+vLLLzVjxgwNGjRI4eHhqlGjhlatWqVChQpJkhYvXqxJkybJy8tLLi4uGjp0qLy8vKwcOQAAAAAgNaKjoxUUFCQnJycNHTpUzs7O2rp1q3r27Klly5bplVdeee4xY2Ji5O/vn+rYnJycVL58+VSPAyQnMDBQUVFR1g4DAADAJjk6Olo7hDRhM8U46dHC3OPGjdO4ceOS3F+5cmWtXbs2fYMCAAAAAFiUo6Ojjh49Knt7e3OyXbFiRV26dElLlixJUTHOwcEhTdpeZpaZuLBd7u7u3BkHAACQhICAAGuHkGZsqhgHAAAAAHgxOTs7P7GtdOnS+vXXX1M0nsFgSHJMwNbQBhUAACBpmWlinNHaAQAAAAAAXmznzp2Tp6en/Pz8Em3/888/0+TuNgAAAACwJopxAAAAAACrKl26tEqVKqXx48fLz89Ply5d0pQpU3TixAn17t3b2uEBAAAAQKrQphIAAAAAYFVGo1E+Pj6aPn26Bg0apHv37ql8+fJatmyZypQpY+3wAAAAACBVKMYBAAAAAKwub968mjx5srXDAAAAAIA0R5tKAAAAAAAAAAAAwEIoxgEAAAAAAAAAAAAWQjEOAAAAAAAAAAAAsBCKcQAAAAAAAAAAAICFUIwDAAAAAAAAAAAALIRiHAAAAAAAAAAAAGAhFOMAAAAAAAAAAAAAC6EYBwAAAAAAAAAAAFgIxTgAAAAAAAAAAADAQijGAQAAAAAAAAAAABZCMQ4AAAAAAAAAAACwEIpxAAAAAAAAAAAAgIVQjAMAAAAAAAAAAAAshGIcAAAAAAAAAAAAYCEU4wAAAAAAAAAAAAALoRgHAAAAAAAAAAAAWAjFOAAAAAAAAAAAAMBCKMYBAAAAAAAAAAAAFkIxDgAAAAAAAAAAALAQinEAAAAAAAAAAACAhVCMAwAAAAAAAAAAACyEYhwAAAAAAAAAAABgIfbWDuBx//zzj2bOnKm9e/cqIiJCZcqU0ZAhQ1SjRg1J0vDhw7Vp06ZE57i5uWn//v3WCBcAAAAAAAAAAAB4Kpsqxg0ePFhhYWGaOXOm8ubNq9WrV6t79+7atGmTPDw8dP78efXu3VudOnUyn2NnZ2fFiAEAAAAAAAAAAIDk2UybyuDgYB08eFBjx45VjRo1VKJECY0cOVJubm7atm2b4uLiFBAQoEqVKsnFxcX8X968ea0dOgAAAAAAAAAAAJAkmynG5cmTR4sWLVLFihXN2wwGg0wmk+7evaugoCA9fPhQHh4eVowSAAAAAAAAAAAAeHY206YyZ86catCgQaJtO3bs0OXLl1WvXj1duHBBBoNBK1as0P79+2U0GtWgQQMNGjRIOXLkSPHjmkwmRUZGpjZ8GQwGOTk5pXocIDlRUVEymUzWDgMAAMDmmEwmGQwGa4cBAAAAAECSbKYY92/Hjh3TiBEj1LhxYzVq1Ehz5syR0WhU4cKF5ePjo+DgYH3++ee6cOGCVqxYIaMxZTf5xcTEyN/fP9XxOjk5qXz58qkeB0hOYGCgoqKirB0GAACATXJ0dLR2CAAAAAAAJMkmi3F79uzRJ598oipVqmjmzJmSpI8++kje3t7KmTOnJKl06dJycXFR+/btdfr0aVWpUiVFj+Xg4KCSJUumOmZm4sLS3N3duTMOAAAgCQEBAdYOAQAAAACAZNlcMe7bb7/VpEmT9MYbb2j69OnmGa4Gg8FciEtQunRpSVJISEiKi3EGg0HOzs6pCxpIB7RBBQAASBoT4wAAAAAAtixlvR0tZPXq1ZowYYI6duyoL7/8MlGrmSFDhqh79+6Jjj99+rQkpcmdbQAAAAAAAAAAAEBas5liXGBgoCZPnqw33nhDH374ocLCwnTz5k3dvHlT4eHhatmypQ4ePKgFCxbo8uXL2rdvn0aMGKGWLVvKw8PD2uEDAAAAAAAAAAAAT7CZNpW7du1STEyMfH195evrm2ifl5eXpk6dqtmzZ8vHx0c+Pj7KkSOH3nrrLQ0aNMg6AQMAAAAAAAAAAAD/wWaKcb1791bv3r2fekzTpk3VtGnTdIoIAAAAAAAAAAAASB2baVMJAAAAAAAAAAAAZDYU4wAAAAAANiMwMFCenp7atGmTtUMBAAAAgDRBMQ4AAAAAYBNiYmL0ySefKDIy0tqhAAAAAECaoRgHAAAAALAJc+fOVbZs2awdBgAAAACkKXtrBwAAAAAAwNGjR7V27Vp9//33atiwYarHM5lMaXKHncFgkJOTU6rHAZITFRUlk8lk7TAAAABsjslkksFgsHYYaYJiHAAAAADAqu7du6ehQ4dq1KhRKliwYJqMGRMTI39//1SP4+TkpPLly6dBREDSAgMDFRUVZe0wAAAAbJKjo6O1Q0gTFOMAAAAAAFY1btw4Va1aVW+99Vaajeng4KCSJUumepzMMhMXtsvd3Z074wAAAJIQEBBg7RDSDMU4AAAAAIDVfP/99/Lz89MPP/yQpuMaDAY5Ozun6ZiAJdAGFQAAIGmZaWKc0doBAAAAAABeXBs3blRYWJgaNmwoT09PeXp6SpLGjh2rFi1aWDk6AAAAAEg97owDAAAAAFjN9OnT9eDBg0TbmjRpogEDBqh58+ZWigoAAAAA0g7FOAAAAACA1bi5uSW5PV++fCpcuHA6RwMAAAAAaY82lQAAAAAAAAAAAICFcGccAAAAAMCmnD9/3tohAAAAAECa4c44AAAAAAAAAAAAwEIoxgEAAAAAAAAAAAAWQjEOAAAAAAAAAAAAsBCKcQAAAAAAAAAAAICFUIwDAAAAAAAAAAAALIRiHAAAAAAAAAAAAGAhFOMAAAAAAAAAAAAAC6EYBwAAAAAAAAAAAFgIxTgAAAAAAAAAAADAQijGAQAAAAAAAAAAABZCMQ4AAAAAAAAAAACwEIpxAAAAAAAAAAAAgIVQjAMAAAAAPFX//v3l5+eXaFt8fLzOnTunqKioJ47funWrypUrl17hAQAAAIBNoxgHAAAAAHiqPXv26Pr164m23b17V15eXjpx4oR1ggIAAACADIJiHAAAAAAgRUwmk7VDAAAAAACbZ1PFuH/++UdjxozRq6++qmrVqun9999P1ArF399fnTp1UtWqVdWwYUMtWbLEitECAAAAAAAAAAAAT2dTxbjBgwfr5MmTmjlzpjZs2KAKFSqoe/fuunTpku7cuaNu3bqpePHi2rhxoz766CPNnj1bGzdutHbYAAAAAAAAAAAAQJLsrR1AguDgYB08eFBr1qxRtWrVJEkjR47U/v37tW3bNmXNmlWOjo4aN26c7O3t5eHhoeDgYH399ddq06aNlaMHAAAAAAAAAAAAnmQzxbg8efJo0aJFqlixonmbwWCQyWTS3bt39eeff6pmzZqyt/+/kGvXrq2FCxcqLCxM+fLlS9HjmkwmRUZGpjp+g8EgJyenVI8DJCcqKoo1OQAAAJJgMplkMBisHQYAAAAAAEl6rmJc//795e3trRo1api3xcfH68KFCypWrNgTxaitW7dq2LBh8vf3/8+xc+bMqQYNGiTatmPHDl2+fFn16tXTrFmzVLp06UT7XV1dJUl///13iotxMTExzxTff3FyclL58uVTPQ6QnMDAQEVFRVk7DAAAAJvk6Oho7RAAAAAAAEjScxXj9uzZo6ZNmybadvfuXXl5eWnp0qV65ZVX0iywY8eOacSIEWrcuLEaNWqkKVOmPJFgZ8mSRZL08OHDFD+Og4ODSpYsmapYJTETFxbn7u7OnXEAAABJCAgIsHYILwRfX18FBwebf37w4IEMBoO2bNmiY8eOJTr2/Pnz6R0eAAAAANisNGlTmdYFgj179uiTTz5RlSpVNHPmTElS1qxZFR0dnei4hCKcs7Nzih/LYDCk6nwgvdAGFQAAIGlMjEsfu3fv1u7du5/Y/v333yd5PH8vAAAAAPCIzawZl+Dbb7/VpEmT9MYbb2j69Onmu+EKFCig0NDQRMcm/Ozm5pbucQIAAADAi2LKlCnWDgEAAAAAMiybKsatXr1aEyZMUOfOnTVixAgZjUbzvpo1a+q7775TXFyc7OzsJEmHDh2Su7t7iteLAwAAAAD8Ny8vL2uHAAAAAAAZlvG/D0kfgYGBmjx5st544w19+OGHCgsL082bN3Xz5k2Fh4erTZs2ioiI0MiRIxUQEKBNmzZpxYoV+vDDD60dOgAAAAC88MLDw59YWgAAAAAAYEPFuF27dikmJka+vr6qV69eov8mTZqkfPnyafHixQoMDJSXl5e++uorDR06lBmaAAAAAJBOtm/frnHjxiXadvbsWbVu3Vovv/yyqlatqn79+unGjRvWCRAAAAAAbJDNtKns3bu3evfu/dRjKleurLVr16ZTRAAAAACABAMHDtSuXbtkMBg0atQo2dvb6+bNm+ratasiIiLk4eGhEiVK6ODBg+rYsaO2bNmibNmyWTtsAAAAALC65y7G+fr6Kjg42PzzgwcPZDAYtGXLFh07dizRsefPn099hAAAAAAAq9q6dat27dqlFi1aqGfPnrK3f5RK+vj4KDw8XDVr1tTy5ctlZ2enoKAgeXl5admyZerfv7+VIwcAAAAA63vuYtzu3bu1e/fuJ7Z///33SR5vMBieOygAAAAAgO3YsmWLKleurBkzZiTannCnXO/evWVnZydJKl68uN566y35+vpSjAMAAAAAPWcxbsqUKZaKAwAAAABgo/z9/eXt7Z1o26VLl3Tr1i05OTmpVq1aifZVqFBB27ZtS8cIAQAAAMB2PVcxzsvLy1JxAAAAAABs1L1795QvX75E2/z8/CRJ1apVM7etTGAwGGQymdItPgAAAACwZca0HjA8PFzR0dFpPSwAAAAAwEpy586tsLCwRNt+//13GQyGJ+6Kk6SLFy8qb9686RUeAAAAANi0FBXjtm/frnHjxiXadvbsWbVu3Vovv/yyqlatqn79+unGjRtpESMAAAAAwIqqVq2qXbt2mX++d++e9u7dK0l67bXXEh0bERGh7du3q2rVqukYIQAAAADYrucuxg0cOFCDBw/W2rVrFRsbK0m6efOmunbtqvPnz8vDw0Ovv/66fv/9d3Xs2FH3799P86ABAAAAAOmnY8eOOnPmjHr16qVVq1apZ8+eioqKUp06dVSqVCnzcVeuXFG/fv10+/Ztvfvuu1aMGAAAAABsx3MV47Zu3apdu3apRYsW2rx5s3ldAB8fH4WHh6tGjRrasmWL5syZo40bNyosLEzLli2zSOAAAAAAgPTxyiuv6NNPP9Vvv/2mCRMm6OTJkypVqpSmTJliPmbatGlq0qSJDh8+rM6dO6t27drP9RhhYWH69NNPVbt2bXl6eqpXr14KCAhI66cCAAAAAOnO/r8P+T9btmxR5cqVNWPGjETbd+3aJYPBoN69e8vOzk6SVLx4cb311lvy9fVV//790y5iAAAAAEC66969u1q2bKmTJ08qe/bsqlWrljn/k6SCBQuqTp06atOmjZo3b/7c4/fp00dGo1Fff/21nJ2dNXv2bHl7e8vX11dOTk5p+VQAAAAAIF09VzHO399f3t7eibZdunRJt27dkpOT0xMLd1eoUEHbtm1LdZAAAAAAAOtzc3NTkyZNktzXqVMnderUKUXj3rlzR0WKFFGfPn3MbS/79u2rVq1a6eLFi6pcuXKKYwYAAAAAa3uuYty9e/eUL1++RNv8/PwkSdWqVTO3rUxgMBhkMplSGSIAAAAAIDPLkyePZs6caf751q1bWrJkiQoUKKCSJUumaEyTyaTIyMhUx2YwGLgzDxYVFRXFdycAAABJMJlMMhgM1g4jTTxXMS537twKCwtLtO3333+XwWB44q44Sbp48aLy5s2buggBAAAAAFbVpUuX5z7HYDBoxYoVz33e6NGjtW7dOjk6OmrBggVydnZ+7jEkKSYmRv7+/ik693FOTk4qX758qscBkhMYGKioqChrhwEAAGCTHB0drR1CmniuYlzVqlW1a9cu9erVS9KjO+X27t0rSXrttdcSHRsREaHt27c/96LdAAAAAADbcuTIEfOM1Ge9gyelM1i7du2q9u3ba82aNerXr59Wr16tChUqPPc4Dg4OKb6r7nGZZSYubJe7uzt3xgEAACQhICDA2iGkmecqxnXs2FHdunVTr1691KBBA23dulVRUVGqW7euua+/JF25ckWjRo3S7du39e6776Z50AAAAACA9FOoUCH9/fffyp8/v9588021aNFCnp6eFnmshALahAkTdOLECX377beaMmXKc49jMBhSfFcdkJ5ogwoAAJC0zDQx7rmKca+88oo+/fRTzZo1S/v375cklSpVKlFiNG3aNC1dulQmk0ldunThzjgAAAAAyOB+/vlnnTx5Utu3b9fOnTu1atUqFSxYUC1atFCLFi1UtmzZVI0fFhamQ4cOqVmzZrKzs5MkGY1GeXh4KDQ0NC2eAgAAAABYzXMV4ySpe/fuatmypU6ePKns2bOrVq1a5mRJkgoUKKA6deqoTZs2at68eZoGCwAAAACwjipVqqhKlSoaPny4jh49qh9//FGbNm3S4sWLVaxYMbVs2VLNmzdXiRIlnnvs0NBQDRkyRPny5dMrr7wi6dGab2fPnlWjRo3S+qkAAAAAQLp67mKcJLm5ualJkyZJ7uvcubM6d+6cqqAAAAAAALarZs2aqlmzpsaMGaNDhw5p+/btWrlypebNm6eyZcuqRYsWat68uQoVKvRM45UtW1b16tXT+PHjNXHiROXMmVM+Pj66d++evL29LftkAAAAAMDCnqsY16VLl+d+AIPBoBUrVjz3eQAAAAAA22Y0GlW3bl3VrVtX48eP18GDB7VmzRrNmDFDM2fO1NmzZ59pHIPBoC+//FIzZszQoEGDFB4erho1amjVqlXPXNADAAAAAFv1XMW4I0eOmBfMM5lMz3ROZlpgDwAAAADwpNu3b8vX11c7duzQ0aNHZTKZVKBAgecaI0eOHBo3bpzGjRtnmSABAAAAwEqeqxhXqFAh/f3338qfP7/efPNNtWjRQp6enpaKDQAAAABgo27fvq3du3dr586d8vPzU2xsrFxdXdWhQwc1b96cXBEAAAAA/r/nKsb9/PPPOnnypLZv366dO3dq1apVKliwoFq0aKEWLVqobNmylooTAAAAAGBlSRXg8ufPr/bt26tZs2aqXr063VEAAAAA4F+eqxgnSVWqVFGVKlU0fPhwHT16VD/++KM2bdqkxYsXq1ixYmrZsqWaN2+uEiVKWCJeAAAAAEA6W7NmjbkAFxcXp7x586pNmzZq3ry5Xn75ZQpwAAAAAPAUz12Me1zNmjVVs2ZNjRkzRocOHdL27du1cuVKzZs3T2XLllWLFi3UvHlzFtwGAAAAgAxs/PjxMhgMeumll9SsWTPVrl1bdnZ2kiQ/P79kz6tZs2Z6hQgAAAAANitVxbgERqNRdevWVd26dTV+/HgdPHhQa9as0YwZMzRz5kydPXs2LR4GAAAAAGAlJpNJwcHBWrhwoRYuXPhM5/j7+1s4KgAAAACwfWlSjEtw+/Zt+fr6aseOHTp69KhMJpMKFCiQlg8BAAAAAEhn/fv3t3YIAAAAAJBhpboYl9QC3q6ururQoYOaN28uT0/PtIgTAAAAAGAlKSnGrV692gKRAAAAAEDGk6JiXFIFuPz586t9+/Zq1qyZqlevzgLeAAAAAJCJmEwm/fLLLzp69KgkqVKlSmrWrNkTud+NGzc0YsQI/fbbb+rQoYM1QgUAAAAAm/Jcxbg1a9aYC3BxcXHKmzev2rRpo+bNm+vll19O0wLc/PnzdejQIa1cudK8bfjw4dq0aVOi49zc3LR///40e1wAAAAAQGIRERHq3bu3jh07JpPJJEkyGAxaunSplixZoly5ckmStm/frvHjx+vu3bsqUaKENUMGAAAAAJvxXMW48ePHy2Aw6KWXXlKzZs1Uu3Zt2dnZSZL8/PySPa9mzZrPFdTy5cs1Z86cJ847f/68evfurU6dOpm3JTw+AAAAAMAy5s+fLz8/P73yyitq27atnJ2dtXv3bm3evFkzZ87U+PHj9cUXX2jZsmWSpC5duuiTTz6xctQAAAAAYBueu02lyWRScHCwFi5cqIULFz7TOf7+/s903I0bNzRy5EgdO3ZM7u7uifbFxcUpICBAffv2lYuLy/OGDQAAAABIoX379qly5crmYpskvfbaa8qdO7fWrVsnd3d3LV26VAUKFNDnn3+uWrVqWTFaAAAAALAtz1WMS8mi3c/jzJkzypUrl7Zu3ap58+bp2rVr5n1BQUF6+PChPDw8LBoDAAAAACCxkJAQ9enT54ntrVq10rJlyzRz5kzVrVtXM2fONLesBAAAAAA8YlPFuEaNGqlRo0ZJ7rtw4YIMBoNWrFih/fv3y2g0qkGDBho0aJBy5MiR4sc0mUyKjIxM8fkJDAaDnJycUj0OkJyoqCjz+hwAAAD4PyaTKU3Xr8aT7t+/L1dX1ye2J3QtKV++vBYtWsQyAgAAAACQhOduU2ktFy9elNFoVOHCheXj46Pg4GB9/vnnunDhglasWCGj0ZiicWNiYp65jebTODk5qXz58qkeB0hOYGCgoqKirB0GAACATXJ0dLR2CJleUgXPhDysU6dOFOIAAAAAIBkZphj30UcfydvbWzlz5pQklS5dWi4uLmrfvr1Onz6tKlWqpGhcBwcHlSxZMtXxMRMXlubu7s6dcQAAAEkICAiwdggvvHz58lk7BAAAAACwWRmmGGcwGMyFuASlS5eW9Gj9gpQW4wwGg5ydnVMdH2BptEEFAABIGhPjAAAAAAC2LMMU44YMGaJ//vlHS5YsMW87ffq0JKXJnW0AAAAAgOT5+fkpLi4u0bb79+9Lkg4ePKgbN248cU7r1q3TIzQAAAAAsGkZphjXsmVL9enTRwsWLFCLFi0UGBiozz77TC1btpSHh4e1wwMAAACATG3dunVat25dkvsenzQpSSaTSQaDgWIcAAAAACgDFeNee+01zZ49Wz4+PvLx8VGOHDn01ltvadCgQdYODQAAAAAytf79+1s7BAAAAADIsGy2GDd16tQntjVt2lRNmza1QjQAAAAA8OKiGAcAAAAAKWe0dgAAAAAAAAAAAABAZkUxDgAAAAAAAAAAALAQinEAAAAAAAAAAACAhVCMAwAAAAAAAAAAACyEYhwAAAAAAAAAAABgIRTjAAAAAAAAAAAAAAuhGAcAAAAAAAAAAABYCMU4AAAAAAAAAAAAwEIoxgEAAAAAAAAAAAAWQjEOAAAAAAAAAAAAsBCKcQAAAAAAAAAAAICFUIwDAAAAAAAAAAAALIRiHAAAAAAAAAAAAGAhFOMAAAAAAAAAAAAAC6EYBwAAAACwqn/++UdjxozRq6++qmrVqun999+Xn5+ftcMCAAAAgDRBMQ4AAAAAYFWDBw/WyZMnNXPmTG3YsEEVKlRQ9+7ddenSJWuHBgAAAACpRjEOAAAAAGA1wcHBOnjwoMaOHasaNWqoRIkSGjlypNzc3LRt2zZrhwcAAAAAqUYxDgAAAABgNXny5NGiRYtUsWJF8zaDwSCTyaS7d+9aMTIAAAAASBv21g4AAAAAAPDiypkzpxo0aJBo244dO3T58mXVq1cvxeOaTCZFRkamNjwZDAY5OTmlehwgOVFRUTKZTNYOAwAAwOaYTCYZDAZrh5EmKMYBAAAAAGzGsWPHNGLECDVu3FiNGjVK8TgxMTHy9/dPdTxOTk4qX758qscBkhMYGKioqChrhwEAAGCTHB0drR1CmqAYBwAAAACwCXv27NEnn3yiKlWqaObMmakay8HBQSVLlkx1TJllJi5sl7u7O3fGAQAAJCEgIMDaIaQZinEAAAAAAKv79ttvNWnSJL3xxhuaPn16qmfAGgwGOTs7p1F0gOXQBhUAACBpmWlinNHaAQAAAAAAXmyrV6/WhAkT1LFjR3355ZeZphUNAAAAAEjcGQcAAAAAsKLAwEBNnjxZb7zxhj788EOFhYWZ92XNmlU5cuSwYnQAAAAAkHoU4wAAAAAAVrNr1y7FxMTI19dXvr6+ifZ5eXlp6tSpVooMAAAAANIGxTgAAAAAgNX07t1bvXv3tnYYAAAAAGAxrBkHAAAAAAAAAAAAWAjFOAAAAAAAAAAAAMBCbLYYN3/+fHXu3DnRNn9/f3Xq1ElVq1ZVw4YNtWTJEitFBwAAAAAAAAAAAPw3myzGLV++XHPmzEm07c6dO+rWrZuKFy+ujRs36qOPPtLs2bO1ceNGK0UJAAAAAAAAAAAAPJ29tQN43I0bNzRy5EgdO3ZM7u7uifatW7dOjo6OGjdunOzt7eXh4aHg4GB9/fXXatOmjZUiBgAAAAAAAAAAAJJnU8W4M2fOKFeuXNq6davmzZuna9eumff5+fmpZs2asrf/v5Br166thQsXKiwsTPny5UvRY5pMJkVGRqY6doPBICcnp1SPAyQnKipKJpPJ2mEAAADYHJPJJIPBYO0wAAAAAABIkk0V4xo1aqRGjRoluS8kJESlS5dOtM3V1VWS9Pfff6e4GBcTEyN/f/8Unfs4JycnlS9fPtXjAMkJDAxUVFSUtcMAAACwSY6OjtYOAQAAAACAJNlUMe5pHjx48ESCnSVLFknSw4cPUzyug4ODSpYsmarYJDETFxbn7u7OnXEAAABJCAgIsHYIAAAAAAAkK8MU47Jmzaro6OhE2xKKcM7Ozike12AwpOp8IL3QBhUAACBpTIwDAAAAANgyo7UDeFYFChRQaGhoom0JP7u5uVkjJAAAAAAAAAAAAOCpMkwxrmbNmjp27Jji4uLM2w4dOiR3d/cUrxcHAAAAAACAxOLjWSIBlsP1BQB4EWWYNpVt2rTR4sWLNXLkSPXo0UOnTp3SihUrNH78eGuHBgAAAAAAkGkYjQbNW3NQ10LvWjsUZDKFXXOp3/t1rR0GAADpLsMU4/Lly6fFixdr0qRJ8vLykouLi4YOHSovLy9rhwYAAAAAAJCpXAu9q6Brd6wdBgAAQKZgs8W4qVOnPrGtcuXKWrt2rRWiAQAAAAAAAAAAAJ5fhlkzDgAAAAAAAAAAAMhoKMYBAAAAAAAAAAAAFkIxDgAAAAAAAAAAALAQinEAAAAAAAAAAACAhVCMAwAAAAAAAAAAACyEYhwAAAAAAAAAAABgIRTjAAAAAAAAAAAAAAuhGAcAAAAAAAAAAABYCMU4AAAAAAAAAAAAwEIoxgEAAAAAAAAAAAAWQjEOAAAAAAAAAAAAsBCKcQAAAAAAAAAAAICFUIwDAAAAAAAAAAAALIRiHAAAAAAAAAAAAGAhFOMAAAAAAAAAAAAAC6EYBwAAAAAAAAAAAFgIxTgAAAAAAAAAAADAQijGAQAAAAAAAAAAABZCMQ4AAAAAAAAAAACwEIpxAAAAAAAAAAAAgIVQjAMAAAAAAAAAAAAshGIcAAAAAMCmzJ8/X507d7Z2GAAAAACQJijGAQAAAABsxvLlyzVnzhxrhwEAAAAAacbe2gEAAAAAAHDjxg2NHDlSx44dk7u7u7XDAQAAAIA0QzEOAAAAAGB1Z86cUa5cubR161bNmzdP165dS9V4JpNJkZGRqY7LYDDIyckp1eMAyYmKipLJZLJ2GGZc80gPtnbdAwBsk8lkksFgsHYYaYJiHAAAAADA6ho1aqRGjRql2XgxMTHy9/dP9ThOTk4qX758GkQEJC0wMFBRUVHWDsOMax7pwdauewCA7XJ0dLR2CGmCYhwAAAAAINNxcHBQyZIlUz1OZpmJC9vl7u5uU3cIcc0jPdjadQ+8qHjPhyWlxft8QEBAGkRiGzJcMe7atWtJzpacOHGi3n33XStEBAAAAACwNQaDQc7OztYOA/hPtITEi4jrHrAN8fEmGY0U5JD20uraykwF4wxXjDt//ryyZMmiPXv2JPqLyJEjhxWjAgAAAAAAAAAg4zAaDZq35qCuhd61dijIRAq75lK/9+taOwybk+GKcRcuXJC7u7tcXV2tHQoAAAAAAAAAABnWtdC7Crp2x9phAJme0doBPK/z58+nSd9/AAAAAAAAAAAAwNIy5J1xLi4u6tChg4KCglSsWDH17dtX9evXT9F4JpNJkZGRqY7LYDDQ7xoWFRUVxeLGAAAASTCZTJlqLQEAAAAAQOaSoYpx0dHRCgoKkpOTk4YOHSpnZ2dt3bpVPXv21LJly/TKK68895gxMTHy9/dPdWxOTk4qX758qscBkhMYGKioqChrhwEAAGCTHB0drR0C0tDUqVOtHQIAAAAApJkMVYxzdHTU0aNHZW9vb062K1asqEuXLmnJkiUpKsY5ODikSdtLZuLC0tzd3bkzDgAAIAkBAQHWDgEAAAAAgGRlqGKcJDk7Oz+xrXTp0vr1119TNJ7BYEhyTMDW0AYVAAAgaUyMAwAAAADYMqO1A3ge586dk6enp/z8/BJt//PPP9Pk7jYAAAAAAAAAAAAgLWWoYlzp0qVVqlQpjR8/Xn5+frp06ZKmTJmiEydOqHfv3tYODwAAAAAAAAAAAEgkQ7WpNBqN8vHx0fTp0zVo0CDdu3dP5cuX17Jly1SmTBlrhwcAAAAAAAAAAAAkkqGKcZKUN29eTZ482dphAAAAAAAAAAAAAP8pQ7WpBAAAAAAAAAAAADISinEAAAAAAAAAAACAhVCMAwAAAAAAAAAAACyEYhwAAAAAAAAAAABgIRTjAAAAAAAAAAAAAAuhGAcAAAAAAAAAAABYCMU4AAAAAAAAAAAAwEIoxgEAAAAAAAAAAAAWQjEOAAAAAAAAAAAAsBCKcQAAAAAAAAAAAICFUIwDAAAAAAAAAAAALIRiHIAUi483WTsEZGJcXwAAAAAAAAAyA3trBwAg4zIaDZq35qCuhd61dijIZAq75lK/9+taOwwAAAAAAAAASDWKcQBS5VroXQVdu2PtMAAAAAAAAAAAsEm0qQQAAAAAAAAAAAAshGIcAAAAAAAAAAAAYCEU4wAAAAAAAAAAAAALoRgHAAAAAAAAAAAAWAjFOAAAAAAAAAAAAMBCKMYBAAAAAAAAAAAAFkIxDgAAAAAAAAAAALAQinEAAAAAAAAAAACAhVCMAwAAAAAAAAAAACyEYhwAAAAAAAAAAABgIRTjAAAAAAAAAAAAAAuhGAcAAICnio83WTsEZFJcWwAAAACAF4G9tQMAAACAbTMaDZq35qCuhd61dijIRAq75lK/9+taOwwAAAAAACyOYhwAAAD+07XQuwq6dsfaYQAAAAAAAGQ4Ga5NZXx8vObMmaP69eurSpUq+uCDDxQcHGztsAAAAAAAqUCuBwAAACCzynDFuPnz5+u7777TxIkTtXbtWhkMBvXs2VPR0dHWDg0AAAAAkELkegAAAAAyqwxVjIuOjtbSpUv10UcfqUGDBipbtqxmzZqlGzduyNfX19rhAQAAAABSgFwPAGBt8fEma4eATIzrC0CGWjPu3Llzun//vmrXrm3eljNnTpUvX15Hjx5VixYtnmu8mJgYmUwmnTp1Kk3iMxgMavGyi+Li86XJeIAk2RmNOn36tEwm2/ulzTUPS7Hl6x54EfF+D0tIy/f6mJgYGQyGNIgK1kKuhxeRLX/m5ZqHpdj6dR8ZFa04iiZIY3ZGg5ydHG32uuf9HmmNXC9pGaoYFxISIkkqWLBgou2urq66fv36c4+X8JeYln+ZObNnTbOxgMfZ6psO1zwsyVave+BFxPs9LCUt3usNBgO/MzI4cj28yGz1/YtrHpZkq9e9s5OjtUNAJmar1z3v97AUcr3EMlQxLioqSpLk6Jj4F2OWLFl09+7d5x7P09MzTeICAAAAAKQcuR4AAACAzCxDrRmXNeujKv2/F/B++PChnJycrBESAAAAACCVyPUAAAAAZGYZqhiX0LIkNDQ00fbQ0FAVKFDAGiEBAAAAAFKJXA8AAABAZpahinFly5ZV9uzZdfjwYfO2e/fu6ezZs6pRo4YVIwMAAAAApBS5HgAAAIDMLEOtGefo6KhOnTpp+vTpyps3rwoXLqxp06apQIECeuONN6wdHgAAAAAgBcj1AAAAAGRmGaoYJ0kDBgxQbGysRo0apQcPHqhmzZpasmTJEwt9AwAAAAAyDnI9AAAAAJmVwWQymawdBAAAAAAAAAAAAJAZZag14wAAAAAAAAAAAICMhGIcAAAAAAAAAAAAYCEU4wAAAAAAAAAAAAALoRgHAAAAAAAAAAAAWAjFOAAAAAAAAAAAAMBCKMYBAAAAAAAAAAAAFkIxDgAAAAAAAAAAALAQinEA0lV8fLwkyWQyWTkSIHNJ+DfFvy1kRlzXAADYPnI9wDLI9ZCZcV3jRUIxDkC6CQ0NVUREhCTJYDBI+r+EDUDKrF27VufPn1dISIik//u3xQdaZAZ+fn46f/68+boGbElMTIy1QwAAm0GuB6Q9cj1kZuR6sGWWyvXsLTIqAPzL9u3b9fXXXytLliwqU6aM6tatq9dff11GI3MCgJS6dOmSzp8/r23btun+/fuqWrWqmjdvrho1ashgMCg+Pp5/Y8iw9u/fL19fX+3du1cvv/yy8ufPrz59+ih79uyyt+cjLKzrm2++0dmzZ1W/fn0VKFBA1atXt3ZIAGA15HpA2iPXQ2ZGrgdbZslcz2BiOgWAdBIWFqZbt25pxowZunXrliRp6tSpKlGiBL9sgVS4fv26goODNWnSJGXLlk0eHh6aMGGCjEaj4uLiZGdnZ+0QgRQLCAjQ6dOnNXfuXGXLlk2tWrVS27ZtlTt3bmuHhhfY/v37FRISor179+rSpUsqU6aMunTposqVK8vR0dHa4QFAuiPXAyyDXA+ZGbkebJElcz2KcQDSjclkksFg0P3793Xx4kXNnDlT58+f1+jRo/XGG28oS5Ys1g4RyFASZkMm/P/OnTvavHmz1q1bp9y5c2v16tWJ9gMZQXR0dJIfcOPi4jRmzBidPXtWZcqU0dChQ5U3b14rRAj8nzt37igoKEifffaZJKlevXrq06ePnJ2drRwZAKQvcj0gbZHrITMi10NGYolcj2IcAIuZNGmSypUrp5w5c+rVV19N8hfukCFD9Msvv2jatGlq3LixOYkDkLynJVwPHz7Ur7/+qs8//1xFihTRkiVLZDAY+LeFDGHFihU6c+aM6tatq8KFC6tGjRqJ9ptMJn399dfasWOHqlatqiFDhih79uxWihYvmjNnzsjFxUWurq5P7IuOjtb06dN15MgRVatWTUOHDlXWrFmtECUApA9yPcAyyPWQWZHrwZalV65HMQ6AxSxZskRxcXH65ptvVK5cORUrVkzDhw9/oo3CwIED9ccff2jr1q3KkycPHySBp3g8OTtz5ozu3bsnV1dXeXh4mP/txMTEaPfu3fLx8VHTpk3Vv39/K0cNPJsDBw7o5s2b+vnnn3Xx4kWVKFFC3bp1U5UqVRLNqJ8zZ4727NmjPn36qFmzZvzegMVt375dP/30k/744w/Vr19fHh4eev/99xN9+RwdHa158+Zp//79evvtt9WlSxdaRwHItMj1gLRHrofMjFwPtio9cz2KcQAs7vr169q2bZs2btwoSRo7dqyqV69uflOLiIhQly5dVLhwYc2ZM4dfskAyHv8QOmPGDO3evVvXrl3Tp59+qi5duiT6txMZGWluDzRnzhy+/ECGcufOHV29elXjx49XTEyM6tatq759+yaaGdmzZ0/dvXtX69ats2KkeNEcOnRIZ86c0bx581S5cmW9/fbbat26tTkRe/DggcaMGaNLly7p66+/pr0OgEyPXA9IG+R6eFGQ68FWpUeuRzEOQJoKDw9XaGiosmTJoiJFipi3x8XF6datWxo+fLjOnj2rSZMmqWHDhrKzs5PJZNKPP/6odevWaerUqSpUqBAfJIGnWLBggVasWKG5c+eqQIECcnZ2loODg0JCQlS6dGnzcbdu3VLr1q3Vu3dvderUyYoRA8m7dOmSbt68qZiYGFWoUCHRB9rY2FjNmDFDhw4dUpUqVTR06FBly5ZNkhQWFqZ27dqpX79+euedd6wVPl4AsbGxsre3T7QtJCRE48aNU2hoqGrVqqUhQ4aYj4mIiNCbb76pli1b6n//+581QgYAiyDXAyyPXA+ZCbkebF1653qs8AkgzYwdO1Z9+/ZVixYt9NZbb2n9+vXmfXZ2dnJzc9PSpUtVtWpVjR07VpcuXZIkGQwG1a9fXyEhIdqxY4d5G4An3blzR3/88YcmT56smjVr6uHDh1qzZo1atWqlPn36aMyYMZIezazMnz+/evXqpXPnzkl61PYEsCVDhgzRiBEj1KtXL/Xs2VNr164174uLi5O9vb0GDx6sRo0a6dSpU1qzZo1iY2NlMpmUM2dOvfbaa7py5YoVnwEys9WrV2vMmDHq1auXJk6cqIiICEmPrs0CBQro888/18svv6zffvtNCxYsML/HZs+eXSNGjNClS5cUHh4u5j4CyAzI9QDLI9dDZkKuB1tmrVzP/r8PAYD/5u3trQcPHuj9999Xr169FBISotdeey3RMXFxcbKzs9OCBQv0/vvva/To0eZfxrly5dKgQYP0xx9/WCN8IMPIli2b/vnnH23ZskVhYWHy8fFRwYIF1axZMxmNRu3evVtXr141z1YuXbq0Nm3apPDwcOXIkcPK0QP/p3v37goPD9f//vc/OTs7S5J5JqT06Iu9+Ph4OTg4qHfv3rp+/bp+/PFHtW7dWvnz55eDg4MaN26sadOmqUuXLsqTJ4+1ngoyoe7du+vevXtyc3NTrly5FBoaqujoaEn/d23mypVL/fv314MHD7Rv3z7VqFFDr7zyiiTJw8NDFy9eVFBQkCpVqmTNpwIAqUauB6QPcj1kFuR6sGXWzPUoxgFItRkzZujBgweaP3+++ZbzhNt8H29BYmdnZ97+v//9T6NHj9aGDRvUtm1bSVKWLFl08uRJxcbGys7OjhmTeOE9voB3AkdHR3l5eWnVqlXat2+fvL291bRpU5UrV06HDx/Wb7/9JgcHB/Px1apVU61atfTgwQMSNNiMxYsXKzIyUvPnz1f+/PmTPS7h+nd0dNTYsWPVpEkT+fj4aNSoUZKkl156SRUrVky0sDKQWoMHD9b9+/c1b948ubq6Svq/L5kTJFyb2bNn16BBg9S1a1etXbvWnKCVKVNGjRo10l9//UUxDkCGRq4HWAa5HjIrcj3YMmvnehTjAKRKfHy8zp8/r7fffjtR7+eEXroJSdb69evVqlUr8y/RUqVKqXz58jpx4oQ5QWvcuLGqVq36RK9e4EX0eHK2b98+Xb58WZGRkapcubI6dOig1q1bKzo6Wrlz55YkRUdHa8mSJXJxcTF/oJAefbAdOHCgeTYaYAv8/f1Vq1Yt5c+fP9l1Y5YvXy5PT09VqVJFMTExypo1q0aOHKn169fr3r17ypkzpwoXLqzBgwcnmmUJpMbp06d169YtjR492vxeajKZEiVnkhQYGCh3d3fFx8crd+7cmjx5srp37679+/fr1VdflSSVLVtWtWvXTvfnAABphVwPsAxyPWRm5HqwVbaQ67FmHIAUM5lMunr1qo4ePaqKFSuat/3blStXtHDhQvn4+JiPyZYtm7p06aLffvtNwcHB5t67+fLlS78nANiwhORs2rRpGj9+vPbu3Ss/Pz9169ZNixYtkrOzs8LDwzVhwgS99957+uCDD3Tjxg199dVXMhgMidYMIDmDLbl7967OnDmjokWLSno0C+3foqOj9d1332nVqlWSZJ4B7OHhoUuXLumvv/4yH5vwJQWQFs6fP6/g4GAVLFjQvO3fXyB8/fXXmjFjhsLDw2U0GhUfH68SJUqoYcOG+vvvv83HtWvXTm5ubukWOwCkJXI9wHLI9ZBZkevBltlCrkcxDkCKGQwG5c+fX7ly5dLJkyfN2/6tcOHCyp8/v27dumU+Jj4+XqVKlVKJEiUUGxv7RHsGANKWLVu0ZcsWTZs2TUuWLDGvFVC8eHHdvHlThQsXVpkyZVS6dGk1bNhQGzdulIODA/+mYJNCQkIkPVorwMHBQceOHZMkc5urBLGxsXJ0dFTjxo0VGBioBw8emJO4kiVL6vXXX1dQUFC6x48Xw927d5U3b17zHSBJffHs6empvXv3yt/fX9KjL9ScnJxUrVo1/fDDD3rw4EG6xgwAlkCuB1gWuR4yE3I9ZAS2kOvx7g3guY0dO1a//fabpEdvXPny5dO+ffsUHh6e5PFGo1EODg6J+jwbjUY5OjrSqgR4zOMzHCUpICBA9evXV/Xq1bV7925NmDBB48ePV7ly5TR27FhdunRJ7dq102effaYePXrI3t5ecXFx/JuCzdm4caMOHDgg6dH7f6NGjXTkyBHzNoPBYP4gnHD9hoWFyc3NTVmzZk3UNqJMmTK0/kOa+vHHH82fYcqVK6eLFy9q586dkpL+4jlXrlyyt7dXTExMou2enp4qVapUkkkdAGQU5HqAZZDrIbMi14Mts7Vcj2IcgOfm6uqqCxcuSHo06+Xjjz/W77//rgULFiR6U0r4882bN/XgwQOVKVPmiX39+/dXsWLF0jF6wDaZTCbzDMdjx44pKipKkZGRypUrl3766ScNGzZMw4YN07vvvqs7d+7o4MGDiW6RT/DvXteALYiMjNS2bdvM13mjRo304MEDrVixQsePH5eU+IPw3bt3de3aNXNbrMe1bdtWBQoUSLfYkbmdP39eGzZsUPbs2SVJRYsWValSpbR+/XqdO3fOfFxcXJz5s0tYWJg8PDwStTeRHq2R9NFHH8nJySn9ngAApDFyPSDtkeshMyPXg62yxVyPYhyA55YrVy7zLAJJql69uvr27avly5dr7NixCggIkPTol+3Nmzc1atQo2dnZ6Z133jGfk9TsA+BFFR8fb/43MWvWLA0dOlTR0dHy8PDQ8uXLNXDgQI0YMULvvfeeJClPnjx66aWXWB8AGcarr74qR0dHc/uSKlWqaNy4cTp8+LCmT5+ujRs3SpIiIiL0119/adiwYbp//7569OhhzbDxAihTpowcHR3N12DRokXVvXt3HTp0SAsWLDC32LGzs5PBYNCDBw+0ePFiubi4yN3d3TwO6yEByCzI9YC0Ra6HzI5cD7bKFnM9g4k+KgCe08OHD9W2bVu999576tixoyTp9u3b2rlzp7744gvly5dPRYsWNb+RxcfH69tvv5WDg4Pi4uKYzQUk4/jx45o3b568vb1Vr149SdKYMWO0efNmzZo1SyVKlJCDg4PGjx+v+/fva9WqVawXgAwhOjparVq1Up06dTR69Gjz9gMHDmjBggU6d+6cChcurPv378vV1VVZsmTR4sWL+b0BizKZTDIYDJo0aZIiIiI0ZcoU877169drxowZcnFxUePGjVWzZk0FBQXpl19+UVhYmNatWycHBwfFx8fzPgwgUyHXAyyDXA+ZFbkebJGt5noU4wA8F5PJpJiYGI0dO1b37t3TmDFj5ObmZt4fHBys7du3KyAgQHnz5lWZMmXk5eUlOzs7xcbG0t8ceEzChwOTyaQjR46oR48eiouLk4+Pj1599VVJjxZCnjFjhnbu3ClnZ2e5uroqW7ZsWrlyJV8EI0NIuEZ37NihOXPmaMiQIXr99dfN+2/cuKErV67o0KFDcnJyUpkyZVSnTh1+byDd/Pnnn+rYsaMmTJigt99+27z9t99+008//aSdO3cqNjZW7u7uKlOmjEaPHi17e3uuTwCZDrkekHbI9fAiINeDrbO1XI9iHIAUuXDhgtq3b6/33ntPw4YNk6SnflBktgvw3xYtWqSvvvpKTZo00YABA/TSSy+Z9x08eFCRkZHKli2batWqxYdXZDhXrlzRhAkT5ODgoA8//FCVK1d+6vF8+YD0kPDF8+TJk3XlyhUNGjRIlSpVSrQ/PDxcd+/eVb58+cwto/hcAyAzI9cD0h65HjIzcj3YIlvM9bjqATy3+Ph4lS5dWuPHj9eKFSs0d+5cxcbGmn+RxsbGPnEOyRmQtCVLlsjb21uS1KtXL3344Yf67bfftGbNGl27ds18XN26dfXGG2+YZ5HFxcWRnCFDKVq0qDp27KiLFy9q+fLl5v7s0qPfGwl92BOQnCE9GAwGOTo6qnHjxgoNDdV3332nCxcumPfHxcUpZ86cKlq0qDk5M5lMfK4BkGmR6wFph1wPLwpyPdgiW8z1eGcH8NwSfmm2bNlS4eHhmjhxom7evKl27dqpYsWKsre3N7dkAJC82NhY5cyZU3/88YcGDBigOXPmqF+/foqLi9O6detkNBrVsWNHFSpU6Ilz+dIDGVGDBg0UHR2tOXPmaN68eWrWrJneffdd85cNzACGtdSvX1+hoaGaN2+eoqOj1a5dO9WsWdN8PT7+uYbPNwAyM3I9IG2Q6+FFQ64HW2VLuR5tKgEk6XkSrH379mn8+PF66aWXVLp0aQ0aNEj29vZydHS0cJRAxpJUK4aoqCj5+vpq3LhxqlOnjr766itJ0ty5c7VhwwY1aNBAAwYMUP78+a0RMvDMHl8XI+H3R3J/Pnr0qH744Qft3LlT9evXV7NmzdSoUSPuOEK6+PdnnMd/3rp1q9auXavw8HB5eXmpa9euzNwFkOmQ6wFpj1wPmRm5HjIKW8/1KMYBeMLjHyJjYmL08OFDOTo6mhOux/cnvKlduXJFBw4c0MaNG+Xs7CwHBwd16dJFDRs2tNbTAGzK4z2njxw5opdfftm8LyoqSrt379a4ceNUv359zZkzR5I0ZcoUBQcHa8GCBcw+hk17/PdCaGioTCaT4uPjVbBgwUTHPf5BOCIiQsHBwVq8eLEiIiJ0+/ZtNW3aVN7e3nzBhzSV3JoUj1+Pjx/z559/6vfff9fChQv18ssvK0+ePGrTpo0KFSokNze3dI0dANIauR6Q9sj1kJmR68GWZbRcj2IcgEQef4NavHixTp8+rT/++EO1atVS3bp15eXl9dRzJOncuXMKCgpSmTJl5O7unm6xA7boxIkT8vDwUI4cOSQ9Ss66d++uDz74QB9//LH5uPv372vbtm0aO3as2rZtq4kTJ0pKegYaYEsevzZ9fHx04MAB/f3334qNjVWXLl30zjvvKF++fE8932Qyyc/PTx4eHk89Fnhej39G2bt3ry5fvqyQkBA1adJEVatWTXTsv99nQ0NDdfLkSR04cECOjo7q3bs3M9cBZGjkekDaItdDZkeuB1uWEXM9inEAkjRz5kytX79eH3/8sbJkyaKlS5cqKChIu3btUoECBZI8J7nZCMCLbN68edq4caN+/vlnHT16VFmyZNHu3bu1bds2eXl5aeDAgeZjr1y5og4dOujmzZvq1q2bhg0bpoRf0yRnsHWzZ8/WmjVrNHHiRLm7u2vGjBk6cOCAtm7dmuyXdXzxgPQybdo0+fr6qmDBgnJyctLevXs1atQotWvXLsnZuf/+TPPgwQNlzZo1PUMGAIsh1wPSBrkeXhTkerBlGSnXY9VEAE84d+6c9uzZo7lz56pGjRo6cuSIrly5os8//1whISG6efOmKlWq9MR5JGfAk2rVqqVdu3apRo0aevjwoU6fPq18+fLJzs5O69evl8lk0qBBgyRJzs7Oqlu3rjp06KAKFSpIIjFDxhAWFqbff/9dU6dOVcOGDfXTTz/p6NGjmjBhgkJCQnTt2jXVq1fvifO4vpEevv/+e23evFk+Pj6qXLmy9uzZo71798rd3V337t1T/vz5n0jI/t2ijUIcgMyCXA9IO+R6eBGQ68GWZbRcj09TABQfH5/o59jYWMXGxsrT01O7d+/Whx9+qCFDhuj111/XsmXLtHPnTvOt5gCerkaNGqpUqZIiIiKUO3duxcXFqXDhwmrbtq3atGmjtWvXauzYsTp06JCGDh2qGzduqFKlSrKzs1NcXJy1wweS9PjvjaioKMXFxen8+fMqUaKEDh48qE8++UQff/yxWrdurd9++02zZs3S/fv3n/h9A1jCv6+z4OBgNWvWTJUrV9auXbv06aef6rPPPtNLL72koUOHKjg4ONkvmfkSAUBGR64HWA65HjIjcj3Ysoye63FnHPCCM5lM5jelRYsWqUKFCnJyctL9+/e1YsUKLViwQJ988ok6duwoSYqMjFRISAhfTgFP8Xjv/5iYGFWsWFE1a9bU8uXL1aRJE23atElFixZV27ZtlTVrVi1fvlwHDhxQwYIFtXz5chkMBsXHx5sXAQdsyeO/N7766isZjUa1atVKlSpV0rx58+Tr66vhw4erXbt2kh61fMiRI4eyZctmzbDxgnj8+jx8+LDKli2re/fu6Z9//pGvr6/+97//6dNPP1W7du10/vx5nT59WhcuXFCxYsWsHDkApD1yPSDtkeshMyPXgy3LDLked8YBL7DH+zdv2bJFCxYskMlkUrVq1VS5cmV98cUX6tmzpzk5i4qKUnh4uEqWLGnNsAGbFh8fb/53dePGDd27d0/vv/++WrdurVGjRsnZ2VnvvPOO7t27p6JFi6pbt2764YcfNG/ePK1cuVIODg6KjY2lFRBsVsL1vWPHDm3evFmvvvqqChcurOLFi2vLli1q3ry5OTmLjo7WpUuXVLx4cStGjBfF459rvvrqK02cOFG3b9+Wh4eHDh8+rKFDh2rw4MHq0KGDJClLlizKmzev8ubNa82wAcAiyPWAtEeuh8yOXA+2KrPkegYTvQeAF97y5cv1559/qmLFivL29pYknTx5Ul988YUCAwPVq1cvxcfH6+DBgwoNDdXmzZtlb8+NtcC/Pd6Het68edq9e7f+/vtvdejQQb169VK2bNl07NgxjRs3TpGRkfLx8dGRI0f0+uuvy83N7YkxAFu1a9cuLVu2TKVKldKECRPM2/v06aNTp06pcuXKKly4sM6cOaPw8HB9//33sre3ZxFvpIt9+/Zp8eLF6tatmxo1aiRJ6tGjh44dO6bRo0erVq1aio2N1aRJk3T//n2tXLmS910AmRa5HpA2yPXwoiDXgy3L6LkexTjgBZTwATDhF+XAgQO1a9cu1axZU19++aXy5cunuLg4Xb58WYsWLdLhw4eVP39+FS9eXJMmTZKDg4Pi4uJoqwAkY/r06Vq/fr169uwpg8GgmTNnqnfv3urevbucnZ117NgxTZo0SWfPnpWHh4e2bt3KvyfYtH9/ceDj46O1a9cqKipK27dvTzTbbP78+Tpz5oxiY2NVokQJDRkyRPb29oqNjeXLPVjE44m/n5+fJk+erMuXL2vp0qWqXLmypEfXcI8ePRQUFKQbN26oVKlScnR01KpVq/hcAyBTIdcDLItcD5kNuR5sWWbL9SjGAS+wQ4cO6ZVXXpEkTZw4Ud9++61GjBghLy8v5ciRw3xcWFiYcubMKXt7exkMBn7JAk9x6NAhjRkzRrNmzVLFihXl5+enTp06SZI6d+6swYMHy8nJSffu3dPJkydVp04d2dnZMUsSGcKePXtUu3ZtZc+eXRs2bND8+fPl4eGhiRMnmmf8Sv+3qHLCNc3vDaQHk8mk2NhYLVu2TIsXL1a5cuX01VdfJfpM88cffygkJESurq7y9PSUnZ0d1yeATIlcD0h75HrIzMj1YMsyS65HMQ54Qfn5+albt2567733NHLkSEnS8OHDtW3bNo0aNUotWrRQ9uzZJSWeJcNt58DTbdiwQRs3btSaNWt07tw5TZ8+XS1btpSjo6MGDx6svn37qkGDBqpSpYr5HFuapQMk5+rVq3r99dfVpEkTTZ48WdmzZ9eqVau0YcMGFSlSRKNGjZKbmxvXM6xi0aJFunjxoiZPniyj0ajly5drw4YNqlSpksaMGWP+TPNvXK8AMiNyPcAyyPWQWZHrwZZlplyPaRnAC6po0aL64IMPtGfPHk2dOlWSNGXKFLVo0UKTJ0/Wjh07FBERIUmJZnCRnAH/J2E+y+PzWuzt7WU0GnX79m39+OOPKlmypGrXrq3y5cvLzs5O8+fP144dOxKNY2sfDoCkFClSRIsXL9Zvv/2m0aNHKyIiQh07dlTbtm117do1TZo0SSEhIVzPsAoXFxf98MMPmjJliuLj49W1a1d5eXnJ399fEydONH+miYuLS3Qe1yuAzIhcD0g9cj28SMj1YMsyU65HMQ54ASR1A6ybm5s6duwoLy8v/fjjj+YkberUqWrevLlGjx6tw4cPp3eoQIYRHx9v/sIiJiZG0dHRio6OVuvWrfXZZ5/JZDLpwIEDql27tgoUKKC4uDi9+eabWrhwoT799FMrRw88XXKNE+rVq6fZs2dr7969iZK0Nm3a6OTJk1q9enU6R4oXUUJrnMd5eXlp5syZWrt2rSZNmiSTyaQPPvhAb731ls6dO6dPPvlEUVFRNpmQAUBqkOsBaY9cD5kZuR5sWWbP9WynYSaANJfQZiQ+Pl52dnZav369Hj58aO5p7urqqvfee0/x8fFat26dsmTJoo8//lhTpkzRSy+9pAYNGlj5GQC26fF2PitXrtTx48d1+fJl5c2bV8OGDZOHh4eOHDmiv/76S4UKFZLJZNK0adMUFxenV199VQaDwSZvlwcS1o1xcHCQ9KgdxN27dxN9qVC3bl3Nnj1bAwYM0IQJEzRy5Eh17NhRLi4uaty4sbVCxwsg4XNNwvvvmTNnVKFCBfP+5s2by2QyaejQoZKkESNG6IMPPtD9+/cVEhKiLFmyWCVuALAEcj3AMsj1kFmR68GWvSi5HnfGAZnU5cuXNXPmTMXGxsrOzk5hYWHatWuXVq9erY0bN5qPc3V1VefOnVWuXDktXLhQo0ePliT16dNH9vb2io2NtdZTAGzS48nZ9OnTtWDBAlWuXFnvv/++/vzzT/Xp00e3b99WkSJFVKpUKXXo0EEtW7bU9evXNX/+fBkMBplMJpIz2Jzbt29r1apVCgoKkiT9/fffcnBw0JIlS+Tj42M+zmQy6dVXX1WPHj20ZcsW/e9//1NUVJSaNGkiOzu7J1pDAGnh8uXLCgwMNP98/PhxtWnTRqtWrUp0XIsWLTRp0iStW7dO8+bNU1xcnAYMGKCpU6fKaDQmOdMSADIacj3AMsj1kFmR68GWvUi5HnfGAZmUwWDQ7t27dfHiRbm5ualevXoaNGiQli1bpuXLlys+Pl7vvvuuJClfvnwqU6aM4uPjFR0dnegDqL09bxOAJO3bt08NGjQw/9s4e/asfv75Z82ZM0c1atTQ3r17FRMTo4EDB+ry5csqWbKkxo8frz///FMPHjxQp06dzF968O8KtsjJyUk7d+6Ur6+vKlasqGzZsmngwIEyGAz6/PPPFRcXp379+plb9uTMmVPNmjVTeHh4ollofPkAS9i2bZv2799vXsuiUKFC+vDDDzVlyhQZjUa9//775mNr1qyp3Llza+HChcqZM+f/Y+8+46OoGreP/za90kkQCB3pRaqgoiiiUqQLoSNFQJpACAFC7wFCDb1L7x0hSBVQaSrSe4dAIAVC2u7zgidrAnh7338Tstlc3zfC7sx8zsqZOeeaOXMO7du3B17cXEi8NpKISFqlrCeSvJT1xNop64klS09ZTy2EiJXKkSMHPXv2ZNiwYYSFhdGgQQNKlixJu3btmD9/PkuXLsXW1paGDRsSExPD7du3qVWrljm0JQ5pIumdt7c32bNn5/333zd3Pp88eUJUVBQVKlRgz5499O3bl379+lGzZk169epF3rx56devHyVLljQfJz4+XuFMLJazszObN2+matWqXLx4kSlTpuDu7k7z5s0xmUyMHz8eOzs7mjdvjoODA0ePHqV27drUrl0bULshKatWrVqsXLmSL774AoB169bx7bffAjBs2DCMRiMtWrQAXtTlevXq8fHHH/POO++Yj5Fwc0FEJK1T1hNJPsp6kh4o64klS09ZT62EiBUymUzY29tjMBiwtbUlV65cBAUFMXnyZEqWLEn79u2ZO3cukydPZuvWrURGRhIVFcXEiRPN+6uRFXmhefPmPH/+nHHjxiUZBebg4EDWrFmZN28eM2bMoH///jRt2pSYmBgePXpEtmzZXjmWRpGJJTMajVy6dAmA3LlzM2PGDPLmzUvRokVp2bKlOaStW7cOg8GAvb09n332mXl/tRuSkvLly0flypXZsmULb7/9NgaDAQcHB7p06YLBYGDUqFGEhIRQokQJ1qxZw9OnT/H19QXQKHURsSrKeiLJR1lP0gtlPbFk6SnrGUwmkym1CyEiyePlkSr37t0jJiaG3377jZkzZ/LWW28xffp0nJ2dOX/+PPv37+fkyZN4eHjg7++PnZ2dFhoWScTb25vo6GiWLVuGs7MzsbGx5sWOIyIiaNSoETdu3KBXr1507twZgJiYGNq2bctHH31Ep06dUrP4Iv/odSMcY2NjiY6OplmzZsCL9TKKFi0KwJEjR9i3bx+ZM2emQ4cOajckRSUs4p1g7dq1ZMqUidGjR+Ph4cG4cePImzcvz549Y8mSJUydOpW33noLT09PFi9ejL29/SvHEBFJq5T1RJKXsp5YO2U9sWTpNevpYZyIlUjcyO7fv5+QkBDy5ctHhQoVeP78OVu3bmXBggXkzJmToKAgHBwcePbsGS4uLuZjpLXRBCIpKWG6hrlz5+Lm5pYknF26dIlChQpx6dIl2rZtS+7cualRowbZsmVj48aNPHr0iA0bNuh8EouWuN3YvHkzZ86coVChQlSuXBkvLy/u379P+/btMRgMTJgwgXz58vHkyRM8PT3Nx1C7ISklcf28ceMG7u7uuLi44OjoyKVLl+jYsSOenp4EBATg5eUFwP3794mMjCR//vzY2NiofoqI1VDWE0leynpi7ZT1xJKl56ynh3EiViDxSIDx48ezdu1a3NzcuHPnDkOHDqVZs2bExMSwZcsW5s2bh5ubG46Ojnz++ee0bNnylWOIpHfjxo1j4cKFrF+/nuLFixMdHW1etLhr1648e/aMWbNm4eTkxLVr1/D39+fOnTtkzJiRPHnyEBAQgL29vUaRicVKfM0fN24c69atw8vLi4sXL1K/fn1at25NoUKFuH//Pl9//TWRkZFkypSJd955h6FDh6Zu4cXqJQ5n06dP54cffuDJkyd89dVX1K9fHy8vLy5fvkzHjh3x8PCgT58+HD9+nJo1a1KgQIFXjiEikpYp64kkL2U9sXbKemLJ0nvW08M4ESsyc+ZMlixZwrRp0yhSpAgDBw5k165dSULazp072b59O5GRkSxcuNA8+ktE/rJixQo2bdpExowZ6d27N0WKFAGgR48eXL16lZkzZ5I7d25zByAmJobIyEgMBgOZMmXCYDCk2VE6kr4sWrSIefPmMXXqVMqVK8fIkSNZt24dX375Ja1bt6ZgwYKEh4czfvx4YmNjGTVqlOq1vDEBAQGsWrWK3r17c+fOHdatW0f9+vVp3rw5Xl5eXL16lfbt2xMaGkqhQoVYtWqVboqJiNVS1hNJHsp6kl4o64klS69ZTw/jRNKwhNEuJpOJJ0+e0LNnT1q2bEnNmjU5ceIEvr6+vP322/z4448MHTqUpk2bvrKvOpEif0k8gmzDhg2sXLmSjBkzMmLECAICAjh//rw5nL1un//0mYglSDyCLD4+nm7dulGxYkW+/vprfvvtNwYOHEjJkiUJDg7m888/p02bNhQuXDjJMdRuyJtw6NAhhg0bxtSpUylWrBh//vknjRo1Ilu2bNSuXZvWrVuTK1cuIiMj+eWXX/jwww+xtbVN06MkRUQSU9YTSV7KemLtlPUkrUjPWS9tl14kHUvcAQwJCcHGxoYTJ07g7u7OgwcPWLlyJY0bN2bChAm8++67DBs2jGHDhnHz5k0Ac7BTIyvyF4PBgNFoBKBBgwY0bdqUsLAwGjRowKlTp1ixYkWScJawz+uOI2JpTCaTueN64cIFnj59yqVLl8iQIQMPHjxgzZo1fP7554wdO5YGDRqwceNGfH19+emnn5IcQ+2GpISEa2+Chw8fkjVrVgoVKsTZs2cJDAxk4sSJdOjQgcWLF7N06VJ+/vln3Nzc+Pjjj7G1tSU+Pj7NhzMREVDWE0kJynpizZT1xJIp6/0l7f8CkXTIaDQmmf/Zz8+PqKgoevfuTcaMGdm/fz9Go5H3338fZ2dnMmbMSNGiRbl27Rq5cuUyH0edSJG/xMfHA2BjY2PuKDRs2BBvb29y5MhBjhw5ePz4MfBqR0LE0iVuN8aOHUuvXr3IkCEDXbp04e233+b48eM8fPiQd999FwAnJyeKFCnCRx99ZP4M1G5Iykh882DBggWcOnWKqKgoMmXKREREBDt37jQvON+kSRNcXV354Ycf2Lx5s3l/wCqmLRERUdYTSX7KemLNlPXEkinrJaWHcSJpUMJF7OjRo5w7d46+ffuSI0cOmjRpQpEiRVi1ahXZs2enRIkSREVFERERQe/evVm4cGGSzqeIwNq1azEajeaRNpA0pNWvX5+WLVsSGxvL0KFDuXLlis4jSXMS2o0//viDS5cuMWTIEODFqODSpUuzc+dOPDw8qFChAgAXL16kQYMGdO/ePcm5IZLcEr/9sXbtWqZMmUJ0dDTe3t74+PgQFxfHjz/+SLly5ciWLRu3bt3inXfeoXfv3owYMQLQjQMRsS7KeiLJR1lP0gNlPbFUynqv0sM4kTRq3759dO7cmSdPnpA9e3YA3N3dMRgMeHh4cOvWLfbt20evXr0IDw83j3ZJPCJBJL3btGkTEydOZMyYMZhMpr8NaQ0bNqRp06Y8ffqUMWPGcPHiRZ1Hkubs27ePJk2acOrUKdzd3YG/OrYZMmRgz549LF++nJYtW3Lnzh2aNWtmnubKWkahieVJqINLly7l+PHj+Pn5UblyZQAKFizI2bNnuX37NpUqVeLp06dMnjwZJycn6tSpo5tlImK1lPVE/j1lPUlPlPXEEinrvUqti0galSlTJqpVq8bFixe5ePEigHn+3AoVKnDt2jVGjBjB8+fPWb58OXZ2dsTHx1vdiAKRf6NatWo0btyYo0ePMnLkyP84arJhw4Y0a9aMa9eusXbt2tQstsh/JWE6h4T/fvTRR7Rq1YrIyEj27NlDWFiYeVtvb2+KFy/O2rVryZQpE+vWrVO7IW/U3r172bBhAz/++CMRERHmz0uVKoWnpyfVq1enadOm3L59m8DAQPO6L7pZJiLWSFlP5N9T1hNrpqwnaYmy3l8MpoSzVkQs1t9dgK5fv86wYcM4efIky5cvp1ixYubv7ty5Q1xcHLlz58bGxoa4uDgtxCqSSExMDA4ODsTHxzNp0iQOHjzIBx98QN++fTEYDMTHx5tHiCU+B/fv38/777+v0WNi0V5uN6Kjo3F0dARg6NChrF69mkGDBvHll1/i5uYGvAhyjx8/JnPmzBgMBrUbkmIST1eSmK+vL9u2bWPIkCHUqVMHZ2dn4uPjuX79OgcPHsTR0ZHGjRtjZ2en+ikiVkNZTyT5KeuJNVPWE0umrPef6WGciIVL3Mhu3bqV69evc/v2bcqVK0fDhg25f/8+gwYN4sSJE6xYsYKiRYu+0jBb62gCkf+rxJ2DVatW8csvv7B3717i4+Np1qwZvr6+2NjY/G1IA5J8J2JJEtfV1atXc+LECW7duoWXlxc+Pj5kyZKFwYMHs379egYNGkSdOnXMIS3B33WgRf6txPXzwoULPH/+nCdPnlCtWjUAevXqxcGDBxk6dCiffPIJLi4urxxD118RsRbKeiLJT1lPrJmynlgyZb1/podxImlEQEAAmzZtonr16jx58oQDBw7w0UcfMWXKFC5fvsyoUaP4448/WLhwISVLlkzt4oqkCbNmzWLevHkMGzYMV1dXfvjhB86dO8c777yDv7+/Vb8aL9YvICCAzZs307BhQ3LkyMGwYcOoXLkyQUFBuLq6MnjwYDZv3kzPnj1p1qwZzs7OqV1ksXKJg//kyZPZv38/T548ITY2lvz58zN69Gi8vLzo1q0bR48eZejQoXz88cevDWkiItZEWU8k+SnriTVT1hNLo6z331GLI5IGBAcHs23bNoKCghgxYgRffvklNjY2fPHFF1y7do2CBQvi7++Pl5cXEydOTO3iilg8k8lEeHg4R44coW/fvtSuXZuPPvqIgQMHUqdOHX7++WfGjx+PyWSy2kVjxbqdPHmSH374gcDAQL777jty5cqFs7MzzZs35/LlywAMHz6catWq8eOPP+Lk5JTKJZb0ICGczZkzhxUrVjBgwAC2bdtG8+bN+fXXXwkNDQVg+vTpvPvuu/Tt25eTJ0+mZpFFRFKcsp5I8lLWE2unrCeWSFnvv6OHcSJpwJ07dyhYsCClS5dm586d+Pr60q9fP8qUKcP48eP5+eefyZ8/P4GBgcyfPz+1iyti8QwGA05OTjx69Ii7d++aP3dzc6N169bkyJHD3HlICGkiacmDBw9wcXGhQoUKBAcH07NnT/r168fHH39MYGAgQUFBAEydOpXFixdjMBjQZAnyJsTExPDHH3/g5+dHxYoVOXz4MAsWLGD06NHExsYyffp04EVI++abb6hcuXIql1hEJGUp64kkL2U9sXbKemKplPX+mVocEQsWFxcHwKNHj3B1dWX//v34+fnh4+ODt7c3tra2HDlyhCtXrgCQN29ejewSeY3XnRMJi97//vvv3Llzx9w5tbe3p2TJkuTNmxd3d3d1WsXiva6Ourq64uDgwMKFC/Hx8cHX1xdvb2+eP3/O48ePef78uXnbhHZD6wbImxATE8Pvv/+Oo6MjR44cwcfHh969e9OwYUNu3LjBihUruHr1KgDfffedeQFvERFro6wnkjyU9cSaKetJWqKs98/sUrsAIvKXl+crT1iw8qOPPmLu3Lns2rWLCRMmUKdOHeBFo5w3b17eeuutJMfRyC6RvyQ+r86ePUtkZCQGg4Fy5crRv39/GjRowMSJE+natSv58+cnOjqa8+fP89lnn9GlSxetJSAWLXHdjImJAcDBwYH8+fPz8OFDxo0bZ14nIOE7W1tbPDw8khxH9VtSwuuunU5OTpQvX55ly5Zx9uxZ+vfvT9OmTYEXi3VnzZoVT0/PJPvY2SmyiEjap6wnkvyU9cSaKeuJJVPW+79JX79WxIIlnh5h5cqVnD9/nlu3blG3bl0qV66Mr68vEydO5Nq1a5w5cwaTycSUKVOwtbXlgw8+SOXSi1imxOfV5MmT2bFjBwBPnjwhX7589OvXj5kzZ9KtWzfOnz+Pra0tTk5OREREMH36dIUzsWiJ6/e8efP47bffuHz5Mh999BFNmzZl6tSpfPXVV5w9e5ZVq1bh4eHBkiVLiIuLMwc2kZSS+Np5+vRpHj16hKenJwUKFKBRo0a0b9+ed999l2rVqgEQERHB7t27yZ8/vxaYFxGro6wnkvyU9cSaKeuJJVPW+78zmPROtkiqS3wRCwgIYN26dVSpUoWIiAgOHz5Mo0aN+Oyzz7hy5QqTJ0/GxsaGbNmykT17dhYsWIC9vT3x8fHm0ZUiktTChQuZO3cukydPplKlSkyZMoUFCxYwf/58KlSowL1799i9ezcPHz7E09OTr776Cjs7O51XYrEStxtBQUEsXryY1q1bc/v2bc6dO0dkZCRTp04lMjKSiRMncv78efLly4eHhwfTpk1TuyFvTEBAAFu3biU6OhqTyUTx4sUZOXIkf/75J/369SNv3ry4ubkRExPD8+fPWb9+Pfb29ro5JiJWQ1lPJGUp64m1UdaTtEJZ73+nh3EiFuT69evMmDGDZs2aUa5cOQC2bNnC8OHDady4Mb6+vty4cYO7d++SIUMGihQpgo2NDXFxcenutV6Rv3P//n08PDwwGAzExcVha2tLz549KVWqFB07dmTXrl34+fnh5+dH3rx5+fnnn+nWrdsrx1HnVdKCmzdvMnnyZL744gtq1KgBwK+//sqiRYu4e/cu8+fPx9bWloiICOzt7cmePbv53FC7ISnBZDKZ16TYu3cvw4cPZ8yYMRQqVIiffvqJdevWERoayqJFi7hx4waHDx8mJCSEggUL0rx5c/O6AaqfImJtlPVE/j1lPUlPlPXE0ijr/Xvp8xGkiAXatWsX9evX59ChQ7i6upo/r1u3Lv369WPJkiWcPXuWPHnyULlyZYoVK2ZeiDU9X8REEouIiGDz5s1cvHjR/HeDwcD58+cpUqQIp06dwtfXFx8fHxo3bsy9e/eYM2cO169ff+VYCmdi6Xbv3s2nn37KgQMHsLe3N39esWJFvL29efjwIb///jsZMmQgV65c5hsXajckJSWEs9WrV3Pq1Ck++ugj3n33XbJly0a9evXo2LEjjo6OzJ07l3LlytGtWzeGDRtG69atzaPUVT9FxNoo64n8e8p6kp4o64klUtb79/QwTiSVJLyUmvDfrFmz8sEHHxAeHk50dDSA+b81atQgc+bM3Lp165XjpNfXekVeJzo6munTpzN27FgGDRrEtGnTAChbtiwDBgygdevWDBkyxDyHup2dHQUKFMDd3T01iy3yXzEajUn+/umnn/LVV18RERHBhQsXzIt6A7z//vs4Oztz7ty5V46jdkPehHXr1jF79myuXr1KXFyc+fMPPviASpUqERwczPPnz1/ZTzfHRMQaKOuJJD9lPbFmynqSlijr/d/pDBVJBUaj0Tya4MmTJwCUL1+eHj168M4779CzZ09u3ryJo6MjALGxsWTIkEGdSJF/kC1bNg4cOMDx48dZv349FStWBF6MOs6aNSt58+alevXqADx79owNGzaQI0cOMmfOnJrFFvlHiedUv3v3Ljdv3gRg+PDh1KlTh1mzZnHkyBFzRzgsLAxXV1e8vLxSrcySfrx88wBg1apV1KxZk1OnTnH06NEkIa1IkSLkzJnT3BcSEbEmynoiKUNZT6yVsp5YMmW95KU140RS0axZs9i5cyeenp7Uq1ePWrVqcfnyZUaPHs3Fixfp27cvJpOJzZs38+TJE1avXq1RBCL/QUxMDH/++Sfe3t44Ozvzzjvv4OfnR+HChVm1ahXLly/n7t275M+fn6ioKAwGA2vXrk33C8hK2hEYGMiWLVuwsbHhww8/xN/fH4BevXqxf/9+6tWrR+7cufn111+5c+cOGzZsSPfTQEjKSrxuwNatWwkLCyNDhgzUrVsXgLZt23L16lWGDh1K8eLFcXR0pGfPnmTOnJnJkyenYslFRFKWsp5I8lLWE2unrCeWRlkv+elhnEgqWbZsGVOnTqVZs2bs378fGxsbGjduTPPmzbl8+TLDhw/n559/pmrVqrz33ns0b94cZ2dnLTQs8pK/C1Z37tyhbt26FC9enGHDhlGgQAEuXLjAjz/+SEREBDlz5qRp06ZaQFYsWuLO78aNG5kwYQJdunTh+vXrrFmzhs8++4yxY8cC0L9/fzZu3EjZsmWpVKkSvXv3BlD9ljdiwoQJLF26FA8PD+7evUubNm3w8fEBoF27dhw5cgQPDw+KFStGWFgYS5YswcHBIUkdFxGxFsp6IslDWU+smbKepBXKeslHZ6vIG5K4E2k0GgkJCWHIkCHUqlWLNm3aMHjwYNasWYPBYMDb25tBgwYxYcIEfv31VwYNGoSzszPPnz/HyckplX+JiOVIfF5t376dy5cvky9fPipUqEDOnDlZuXIl3t7eDBs2DH9/fwoXLkzOnDlxc3MzH0MLyIqlSly/Y2NjcXBwoHv37jRt2pTIyEgKFizIyJEjARg7dixjx47FYDCwc+dOGjdubD6O6rekhMT1MywsjN9++41ly5bh7u7O3r17GTduHEajEV9fXxYuXEivXr3YuXMn7du3p0mTJjg4OBAbG5tkQXoRkbRKWU8k+SnriTVT1hNLpqyXcnTGirwBJpPJfBFbvnw5Dx48YNu2bRQoUACALFmy4O/vz4gRI8whrVmzZvTt25fhw4fTsmVLlixZQqFChVLzZ4hYlMTn1bhx49i4cSMZMmQgJiaGDz/8kE6dOlG4cGFWrFhB06ZN6devH3FxcZQvX54hQ4aYR+ho9LFYosT1e8GCBfz6668cOnTIvCC9m5sbtWrVAmD06NEYDAbGjBnDmDFjiI+PZ8yYMURHR9OgQQNcXFxS7XeIdUoczk6ePMndu3fN61ZkzJiRevXqERcXx8SJEwHw9fVl8uTJtG/fnqCgIHLmzEnVqlVxdXVNzZ8hIpIslPVEkp+ynlgzZT2xZMp6KUsTJouksMQLeE+YMIGAgAAOHTrEgwcPWL9+vXk7T09P/P39yZ07N0FBQQQHB1O4cGEGDBiAp6cn33zzDbGxsWhmWZEXEs6rBQsWsGXLFqZPn84PP/xAhQoV2LFjB3PmzOHWrVsULlyYNWvW4OXlRZEiRRgwYECS/UUsTeKpHObMmcOUKVPIli0bGTNm5ODBg/z666/Ex8fj7u5OrVq1GDRoEBs2bGDGjBkAjB8/nnfffZdZs2YRHx+fmj9FrFTim2PffvstQ4YM4cCBA1y4cAGAzJkz06hRI/r27cvSpUvN613Mnz+fcuXK0b17d44cOZJq5RcRSS7KeiIpQ1lPrJWynlg6Zb2UpTXjRN6QsLAwBgwYQPfu3cmdOzdHjx7F39+fYsWKsWDBAvN29+7dY/ny5XTv3t38Ou/58+dxc3MjV65cqVV8EYuwbt06GjVqBLy4+REVFUW3bt2oVasWTZo04c8//6RPnz4ULlyYc+fO8cEHH9ChQwdy5syZZOofzasuacH58+eZN28eTZo0oVKlSkRGRlKvXj3c3Nzw9/enXLly2NjYEB4ezq+//sqHH36YpF7fv38fT0/PVPwFYm0S3zzYt28f48ePp2/fvtjZ2TFgwAC8vLwYMGAApUqVAuDx48csXbqUo0ePsmjRIhwcHADo2bMnPXv2NL81IiKS1inrifx7ynqSnijriaVR1nsz9DBO5A1Yvnw5s2bNwsPDg8mTJ5M7d26io6PZt28fQ4cOpXjx4syfP/+V/TS/rshfjhw5Qrt27WjTpg1+fn4APHnyhBYtWtCxY0cqVarEtGnTKFCgAB07dqRHjx7s378fLy8vpkyZQsGCBQG0gKykCT/88APz588nJCSEmTNnUrRoUeDFzb6GDRvi7u7OoEGDzCEtQVxcnKbkkRR38OBB9u7dS8aMGenZsycAN2/epEmTJhQoUIABAwZQsmRJACIiInBzc8NgMBATE2MOaSIi1kJZT+TfU9aT9ERZTyyZsl7K0jSVIm9A9erVeeuttzhz5gx37tzBaDTi6OjIRx99xPDhwzl//jz169d/ZT+FM5G/lC9fnlGjRrFixQrGjBkDQKZMmahXrx6FCxfm+PHjPH36lPLlywOQI0cOSpQoQfXq1cmXL5/5OApnkhaUL18eLy8vQkJC2LZtG0ajEYCMGTOyfv16nj17Rq9evcxTRSSws7NTOJMUFR4ezsyZM1m1ahVnz541f+7l5cWaNWu4evUq48aN4+TJkwC4u7tjMBgwmUwKZyJilZT1RP49ZT1JT5T1xFIp66U8PYwTSWYJjWhib731FlOnTqVgwYIMGzaMCxcuYDKZcHR0pFq1avj6+uLp6fnafUXkBQcHB7788kuGDBnCsmXLGDlyJACdOnWiRIkS7Nixg6xZs1KuXDkAbty4wWeffUafPn2wtbXVfOpisV6+9kdHR5MtWzaGDh1K7dq12bt3LwsXLkwS0latWkW5cuUoXLhwahRZ0pGX62eGDBkICAjgk08+4dy5c3z//ffm77y8vFi9ejW//vormzZtSrKfbo6JiDVQ1hNJGcp6Yq2U9cSSKeu9eZqmUiQZJX4ld9euXVy8eJHHjx9TsmRJ6tevz/379+nQoQPwYoHvt99++5VXeY1GY5LX0EXSu5enGomJiWHTpk0MGzYMb29vBg4cCEDnzp158OABrVq1Yv369URERLBu3TpsbW01XYlYpJfr5erVq/nzzz85ffo0n3zyCXXq1CFbtmz4+/tz6dIl6tWrR9u2bV9pI+Lj4zVCUlJE4rp19epVoqOjsbW1pXDhwoSGhjJo0CDu379P48aN8fb2Nu/34MEDsmbNqnopIlZFWU8k+SnribVS1hNLp6yXOtQLFEkGY8eO5dmzZ+aQFRAQwJgxYzh//jyRkZH079+fSZMm4enpybx58zCZTPj6+vLnn38CJHmVV+FM5C9Go9HcgY2JiSE6OhqAJk2aMHjwYFasWGEeNdmrVy+io6NZsmQJTk5OrFmzxjxKUuFMLM3QoUO5dOmS+e8BAQEEBQXh6OjI559/ztSpUxk1ahQODg4MHjyYQoUKsXXrVmbMmMHL46jUCZbkdvPmzSThbPr06fTo0YMuXbrQpEkTevbsSUREBIMHDyZ79uysW7eOVatWmff38PDA1taWuLi41PoJIiLJRllPJGUo64m1UtYTS6asl7rUExT5l5o3b87hw4exs7MDXoyS3Lx5M5MmTWLq1Kl89NFH2NraUrp0aW7evImnpyfz58/n/v37LFmyJJVLL2K5Eo8cXrRoEf3796dhw4b07t2bY8eO8dVXXzF06FBWrlzJ2LFjKVq0KBs3bmTWrFnMmTMHe3t74uLi1HkVi5PQbuTJkweAo0ePsnXrVqZOncqAAQOoWrUqtra2NG/enIsXL5IhQwYGDRpE5syZuXPnTiqXXqxd3bp1Wbx4sfnaOXv2bJYtW0b//v3Zu3cvjRs3Zv/+/YSFhZEjRw6GDRuGh4cHs2fPJjg4OMmxEvpGIiJplbKeSMpQ1hNrpawnlkxZL/XpYZzIv9CiRQuio6NZvXq1ecTjtWvXeOedd3jnnXfYtWsXfn5+DBkyhFKlSjFo0CAOHz6Mp6cn27ZtMy9MLCKvSghnEydOZPbs2VSoUIG2bdty8eJFOnToQFhYGI0bN2bIkCEsX76c/v37Y29vj6enJwaDAaPRqM6BWJzWrVtjNBrZvHkzjo6OAISFheHl5UXp0qXZvn07LVu2ZMCAAVSuXBl/f382b95M5syZmTJlCqNGjTIvkCyS3Ly9vbG3t6dXr17Ai1Hqx44do3fv3rz33nvs3r2bjRs3MnjwYJ4+fcqKFSvw9PTE19eXL774gurVq6fuDxARSUbKeiIpR1lPrJGynlgyZT3LoIdxIv9H3bt3548//iAoKAgnJydzYxkXF4e9vT3btm3D19eXfv368dVXXxEZGcm5c+d4+PAhAFmyZNFCwyL/4MyZM/z4449Mnz6d5s2bkyNHDkJDQxk5ciSXLl3i5s2bNGnSBB8fH27fvp1k8VlNAySWpkuXLvzyyy906dIFJycn8+fR0dHcuXOH9evX4+/vj4+PDy1atMDR0ZGoqCiuXbsGgJubGzY2Nkmm9BFJLt988w0PHz5k/fr1uLm5ERcXR2RkJGfOnKFIkSIcP36cfv360adPHxo2bMjly5eZMmUK9+/fJ2/evPj4+KhfIyJWQ1lPJOUp64k1UdYTS6asZznUeon8H3h7e3PixAmMRiOLFy8mLCzM3Fh6eXmxc+dOfH196du3r3mRS3d3dzw8PMiYMWOSY2laBZG/JA5Y8KLjGhUVxTvvvENwcDA9evSgV69e1KxZk++//54VK1YA0LRpU5YsWWLuvIpYGm9vb86cOUPx4sVZsWIFhw8fNn9XokQJMmXKhL+/P+3bt6d58+YAPH36FBsbG7y8vJIcSzcfJLm1bduW/fv3U6hQIc6dOwe8mHYkS5YslC9fniFDhtC+fXv8/f2TLN7t5eVFpkyZkhxL/RoRSeuU9URShrKeWCtlPbFkynqWRWe4yP+oWbNmREdHc/DgQcaPH8+iRYuYMWMG4eHhwIv5d1u3bm1eyPL333/n4sWL+Pn54ezszPvvv5+axRexWCaTKcm6AUePHuX58+c4OTmxZMkS8+jjFi1a4ODgQEhICI8fPwbAwcHBPJ2DOq9iaerXr090dDT79+/Hx8eHkJAQFixYwJEjRwAoWLAgtWvXxsvLi99//51Dhw6xZ88evvvuO+zt7alXr14q/wKxZt7e3jx//pzRo0dz//59pk2bxm+//Wb+vnLlyjx69IiyZctSp04d4MWUJvv37yd37tzmqdtERKyBsp5IylDWE2ulrCeWTFnP8miCZZH/wfLly3FwcGDBggXY2NhQq1YtYmNj8fPzA6Br165kypQJX19foqOjmTZtGs+ePSNfvny4ubmxbNky82u9Gk0g8heTyWQecbxy5UqmTZvGggULKFOmDK6urowdOzbJ6OOoqChMJhP58+dPchxN5yCW5sSJExQrVoyBAwcCUKVKFbp3726u40ajkffee4/27dtjZ2dHcHAwHTp0oEiRInh6erJq1Sq1G5JifH19efz4MZs2bcLR0RE7OzsWLFjA3Llz6dChA2XLlqVFixbcuXOHH3/8kdq1a1OwYEEePHhAbGws69evN98c0/VXRNI6ZT2RlKGsJ9ZKWU8smbKeZTKYtCqkyP8kNjYWe3v7JBejTZs24efnR8uWLfn222/N05P8/vvvPH36FFdXV0qWLImNjQ1xcXFaaFgkkcTn0ubNm9m7dy+VKlUyh7Fz587h4+OD0WikSZMmODk5sWvXLkJCQtiwYYPOJ7FosbGx2NraYmNjkyRk7d+/n6lTp5IlSxbatGljHkkfHR3NjRs3yJw5M1mzZsVgMKjdkBSRsGB3+fLlzQvMA2zdupV58+aRO3duvv76a8qVKwdAcHAwv/zyC1FRUXh5efH1119jZ2en+ikiVkVZTyR5KeuJNVPWE0ulrGe59DBO5L9kNBr/45QIiUNawqjJ//UYIulN4nMiNDSUPn36cOTIEapWrcr06dNxcXEhPj6ee/fuMXToUK5du4a7uzv58+dn7Nix2NvbaxSZpCmJb0gkDmnt2rWjatWqr2yvdkPelMR17e9C2st0/RURa6GsJ5L8lPUkvVHWE0ulrGc59GhT5L/0Tw1kwjzPAwcOxMbGhi5duryygLcaWZG/JO4MjBw5kmfPnjF37lwGDRrEoUOHWL16NU2aNMHV1ZVcuXIxd+5cQkJCcHZ2xtXVVaPIxKL93VQOiad5+PDDDwGYPn06ixcvJjY21vxZArUb8qbY2NiY62bCegHz5s1j4cKF2NnZUbp06Vf2UTgTEWuhrCeSvJT1xJop60lao6xnOXTWi/wHN2/eJDIyEnjR2Cb+7+vUq1eP0aNHs2jRIjZt2vRGyiiSViV0PH///XeOHTvGZ599hp2dHaNHj6Zs2bKsWLGCzZs3ExUVZd4ne/bsuLm5mTu5CmdiaU6fPs2zZ88wGAzExMQAr7YbCfUX4MMPP6R79+5cvHjRvMi3SEqLj49/7eeJ62adOnXo0KEDt2/fJiAggMuXL7/JIoqIpDhlPZGUo6wn1khZT9ICZT3LpodxIn/j+fPnrF271txgXrt2DfjnRYO//PJL5s6dS/PmzVO6iCJp3vLly2nTpg329vZUqFABeBHcpk2bRqFChVi8eDGbN2/m2bNnr+yrBWTFEu3fv59Ro0YBcOPGDeD1dTVxR7hatWpMmjQJHx+fN1dQSXeuXr3KokWLgL9GOb7upvPLIc3b25tcuXKRP3/+N1ZWEZGUpqwnkvKU9cTaKOuJpVLWSzu0ZpzIf9CmTRv+/PNPKlSoQHx8PDNmzMDe3v6/7hhqWgWR/ywyMhJvb28uXrxIYGAgNWvWTNJx6NmzJ4cPH2bs2LHUqFEjlUsr8p/FxcUxc+ZMdu3aRVxcHDdv3uT333/HaDT+bVvw8hQnmpddUsqpU6fw8/Pjs88+4+nTp3z66adUqlTpb7d/3fQ7WtdCRKyJsp5IylLWE2uirCeWTFkv7dD/YZHXSHhGvXjxYpycnDhw4ABVq1bFwcHhfxqhpXAm8hej0Zjk73Fxcbi5ubFq1SoKFChAYGAgx44dM29nMBiYMmUKzZs3p3r16qlRZJH/iZ2dHd27dydTpkxcv36datWqYWNjg52d3X+cKiIxhTNJKQULFqRmzZqsXr2apUuXkiFDBuDVa3OCxKMmEyiciYg1UNYTSX7KemLtlPXEkinrpR36vyzykoTRAc+fP+fhw4cYDAaKFSvGnDlz2LFjh3leaBH57yUeYbNp0ybGjx9P//79Wb16NS4uLqxbtw5bW1uGDRvG8ePHk4S03r17Y2tr+7cdXJHUltCJjYuL4+HDh3h4ePDVV19x584dBgwYwPPnz1WHJVUZjUbc3d3JkiULUVFReHl5sW3bNvO1+T+FNBERa6KsJ5L8lPXEminriaVT1ktbNE2lSCKJO5GxsbHY29ubv2vbti3nzp1j6NChVK9eHUdHR/N3r3u9V0ReNWHCBDZu3Ejp0qWJjo7mp59+ombNmowePRobGxsaNGiAg4MD/fv3p2rVqjqvxOIlbjciIyNxc3MDXrQL06dPZ9euXZQqVQp/f3+cnZ1Ts6iSDr081cjp06cB2L17N3v27OG9997Dz8/vtduKiFgbZT2RlKWsJ9ZGWU8smbJe2qSHcSL/X+KQtXTpUn7++Wdy5MhBlSpV+OSTT4AXIe3ChQsMGTKEKlWqcPXqVcqUKZOaxRZJM/bt28ewYcMIDAykbNmyABw8eJBvv/2WunXrMmrUKCIjI/nwww+pXr06EyZMSN0Ci/wPZs+ezf79+4mMjKRNmzY0atSI58+fM2/ePHbv3k3JkiXp06cP58+fp0qVKqldXEkHEgeuI0eOEBUVRd68eSlYsCChoaHMnTuXgwcP8sEHH+Dr65vKpRURSVnKeiIpS1lPrJmynlgaZb20Sw/jREgazgIDA1m6dCmVKlXi6tWruLi40KZNG+rXrw+8WOj7jz/+IFOmTLz99tvMnDlTI7pE/gtLlixh3759LFiwAJPJhMlkwsbGhm3btuHj48O8efOoWrUqz58/x97eXvOpi0VL3PmdOnUqS5cupW7duty9e5e9e/fi6+tLu3btzCFty5YtXL9+nXz58rFjxw61G/LGjB8/npUrV2JnZ8ezZ88YOXIk9evX58mTJ8ydO5d9+/ZRvHhxnjx5QsuWLfnwww9Tu8giIslKWU8k5SnriTVR1pO0Qlkv7dGKwyL8NU/ub7/9xunTp5k7dy7ly5fn9OnTzJo1i8WLFwNQv359Fi9eTFBQEM+fP6dHjx5qZEVecuDAAW7evMnjx48pWrQoH374Ifb29kRGRnLjxg0eP35M5syZzXOvlypVigwZMhAREQGAk5MTAPHx8QppYrESwtnFixeJjIwkKCiIihUr8vz5c+bPn8/48eMBaNeuHR07dqR8+fLcunWLBg0amBdLVvshKSFx3Tp69Cjbtm1j1qxZ2NjYsHv3bgYMGIDJZKJBgwZ06tQJe3t7jh49SlRUFFWrVk3l0ouIJD9lPZHko6wn6YGynlgqZb20Tw/jRP6/jRs3snPnTp49e0bRokUBKFmyJB06dGDu3LksXrwYg8FAvXr16Nq1q3m/uLg47Ox0KokAdO7cmZCQEJ4+fcrDhw+pVasWH330EQCFCxfm6dOnbN68mfr165MxY0YAbG1t8fDwIFOmTEmOpXAmlm7//v306tULV1dX6tatC7y4wdCuXTtMJhMBAQEYDAbatm2bZLoStRuSkhLC2Zo1a7h06RINGjSgUqVKABQpUgSTycTAgQMBaNCgAV27dqVt27ZkzJgRg8Gg+ikiVklZT+TfU9aT9ERZTyyRsl7ap//7Iv9ffHw8V69e5f79+/z555/mi1nZsmXp1KkT8+fPZ8KECWTNmpX333/fvJ8uYiIvdO7cmUePHhEYGEjWrFlxcXHhwYMH5nPk008/Zd++fQQGBhIeHs4HH3yAk5MTEyZMwMXFhYoVK6byLxD533h6elKnTh02bNjA7du3KVWqFEajERcXF9q3b4+NjQ1jx47Fw8ODWrVqmfdTuyEpLSQkhB9//JG9e/fy1VdfAS9GUbq7u9O9e3cMBgODBw/m+fPneHt74+DgALyYkkf1U0SskbKeyL+jrCfpjbKeWCplvbRNa8ZJupR4/ufE9u/fz/jx48mRIwddu3alfPny5u+OHTvGgQMH6Nmzp0Zxibxkx44dLFmyhAkTJpArV67/uO2kSZPYuXMnN27coEiRIri6urJ48WLs7e01XYlYrL9rN+7fv8/o0aPZvXu3eS2MhKkjnj59yg8//MCXX36pTq+kqNdNhXP27FlmzpzJgQMHWLJkCaVLlzbX44iICEaPHs2NGzdYtmxZKpVaRCRlKOuJJC9lPbF2ynpiyZT1rIsexkm6k7iRDQ4O5sGDB1y5coWGDRtSvHhxDhw4QGBgIDly5KBjx46UK1fulWOoEymS1KRJk7hw4QKzZs36223mzp2LwWCgQ4cOXLp0iUePHuHu7k7RokWxsbHR6/JisRK3Gxs2bODatWtcvXqV8uXL07hxY2JjYxk6dKg5pFWpUuWVQKf6LSklcV0LCQkxr9WSPXt27t27h5+fH6dOnWLFihUULVrUvP2zZ89wcnLCxsZG61qIiNVQ1hNJfsp6Ys2U9cSSKetZn1cf+4tYuYSLWEBAAGPGjOHHH3/k9OnTNGnShOnTp1OtWjW6dOnCvXv3mD9/Pj///PMrx1A4E0nq9u3buLq6AhAbG/vK9yaTiWvXrrFy5Uri4uIoVKgQlStXpnjx4tjY2Oh1ebFoiduNiRMnEhUVhbOzM1OmTOHbb78lU6ZM9O3bl08//ZROnTqxf//+V0ZWqn5LSjCZTOa6Nm3aNLp3707Tpk3p1q0b3bt3x8PDA39/f8qVK0fz5s05d+6cOZC5uLiYr78KZyJiLZT1RJKfsp5YM2U9sVTKetZJD+MkXdq4cSMbNmxg+vTpzJs3j759+xIfH0/58uV58OABNWvW5JtvvuH06dMcPHgwtYsrYvFcXFw4ffo0APb29hiNRvN3CY1/7dq1efToEXfu3EnyPfDaKSFELMm+ffvYsWMHQUFBDBgwgM8//xyTyUSzZs24fPkyOXLkwNfXl4oVKzJnzpzULq6kEwnBKigoiOXLl9OpUyd++OEHcuXKxe7duzl37hwFChRgyJAhlCtXjvr163P9+vUkgUzXXxGxNsp6IslLWU+snbKeWCJlPeukfxFJF17uDN68eZMaNWpQrFgxtm7dSqdOnfD398fT0xM/Pz8ePXrE559/zrhx4/juu+9SqdQiaUeDBg148OABAQEBwIsGPz4+3vxngAsXLlCkSBFy5MihDoFYvJfbjZCQEHLmzEnp0qXZuXMnvXv3xsfHh3LlyhEQEMDBgwd56623GDlyJEuXLk2lUkt6kTDLvMlkIjQ0lIMHDzJkyBA+/vhjLl26xN69e5k0aRJRUVGsXbuWPHny0KdPH9q2bfuPa72IiKQ1ynoiKUtZT6yNsp5YMmU966YWUqxe4td6Dx06hMlk4saNG4SFhXHs2DEGDx6Mj48PLVq0wM3NjZ9//tk8Xcm7776Lra2tuaMpIq+XP39+vvjiC7Zv325eSyDxFD/Pnz/n4MGDFClSBAcHh9Qqpsh/JXG7sX37dp48ecLjx49xcHBg7969+Pn54ePjQ/PmzXFycuLkyZNcuXIFgJw5c5qngxBJCYmnGomNjcXW1pbHjx/z9ttvs2fPHr799lv69u1LrVq1CA4OZs2aNTx//pxixYrRv39/7OzsiIuLS+VfISKSPJT1RFKesp5YE2U9sWTKetZPk9qKVUu80GVQUBBr165l3rx5fPrpp4waNYrg4GAGDx5M06ZNAQgLCyNXrlzkzp07yXG0boDIf5Y5c2Y6duzI48ePWbp0KZcuXaJLly7Y2dlx69Ytli5dSkhICLNnzwbQArJisRK3GzNnzmTWrFls2rSJmjVrEhQUxOHDhxk/fjxffvkl8KKD/Lp2QyOCJSUkvnkwfvx4bG1t+eabb4iJiWH8+PGcOHHCfPMAIEuWLBgMhlduGGhdCxGxBsp6Im+Gsp5YC2U9sWTKeumD/nXEqiVcxHbu3MnVq1cZPXo0BQoUwNXVlZIlS3Lp0iWeP39OVFQUd+7cYdKkSWTLlo2SJUumcslFLFPizitAfHw8tra2mEwm8ufPz6BBg9i2bRvff/89Bw8eJDw8nFKlSpEjRw7Wr1+PnZ2deR8RS5RQv3fv3s2tW7eYMWMG+fLlw2Qy4ePjw4QJE/jtt9/InTs3RqPRvGZAjRo1UrPYkk4k3Nj65Zdf2LlzJ/7+/ri5udG9e3eGDx/Oe++9R/PmzTGZTMTGxnLo0CHy58+Pi4tLKpdcRCT5KeuJJC9lPbF2ynpiyZT10geDKWEiUhErde7cOb755htCQ0MJCgrigw8+AODy5csEBQVx5MgRIiMjyZUrFxkzZmTp0qXY29urEynyH2zatIl69eol+SzxCMiYmBh+++03oqKiyJ8/P7lz58ZgMBAXF6dROmLRTCYTT548oUqVKgB0796db7/9FoBHjx6xd+9eAgMDiY6OJnv27Lz11lvMnj1b7Ya8MXPmzGHz5s0ULlyYwMBAAB48eMDKlSsJCgqiWrVquLi48PDhQ8LCwli/fj329vYapS4iVklZTyT5KeuJtVLWE0unrGf99DBOrM7LF6DHjx8THBzMpEmTqFixIlOnTk3yXWhoKGfOnCFXrlyUKVMGW1tbdSJF/oObN2/SrFkzunfvTrNmzV75/uURlf/0uUhqe13dvHr1Kq1atSJbtmwMHTqUsmXLmr8LDQ3l5s2buLm5kT9/fmxsbNRuyBvzyy+/8PXXX2Nvb8+8efMoX748AE+fPuWXX35hxYoVuLu7kzt3brp3725eN0D1U0SsgbKeSMpS1hNro6wnaYmynvXTwzixKokb2evXr+Pq6krWrFkxGo2sX7+ekSNH8vnnnzNu3DiA145s0WgXkf/s2bNn9OvXDxcXF8aPH5/axRH5VxK3G3/++ScGg4EMGTKQO3duLl26RLNmzShevDh+fn4UK1bsH48hkpxerlsxMTE4ODhw6tQpWrVqRZUqVejXrx+FChUyb/NyP0b9GhGxFsp6IilPWU+sibKeWDJlvfRJD+PEaiS+iE2fPp2dO3cSGhpK48aN8fb2JkeOHKxdu5bhw4dTu3Ztxo4dC+jCJfKf/N2r7idOnKBt27ZMmTKF6tWrp0LJRP69xO1GYGAg69evByBbtmyMGDGCkiVLcvHiRby9vSlZsiT9+/enaNGiqVlkSUcS1881a9Zw/vx5bG1tadmyJV5eXvz666+0a9eOjz76iO+++46CBQsC6teIiHVS1hNJfsp6Ys2U9cSSKeulX3q0L1Yj4SIWEBDA4sWLadWqFc2aNWP16tUsWLCAe/fu0bhxY4YMGcIPP/xAly5dAHQRE3mNZcuWcfbsWXM427ZtG7t37zZ/X7ZsWT799FMOHDhAfHw8RqMxtYoq8n+WOJytXLmSIUOG4O/vT3x8PL6+vpw+fZrChQuzYsUKzp49S79+/bh+/Xoql1rSA5PJZK6f48aNY8KECZw7d47Dhw/Ts2dPbt26RcWKFVmwYAH79+9nypQpXLhwAVC/RkSsk7KeSPJR1pP0QFlPLJWyXvqmh3FiVQ4fPszu3btZsmQJTZs2pUaNGoSFhbFt2zbmzp3LgwcPaNSoEb179yYyMlKdSpHX+PnnnxkxYgTff/8958+f5/Hjx4wcOZLhw4fTqlUrfvrpJ6Kiovjyyy/Ztm0bISEh2NjYoBetJS06e/Ys+/fvZ9asWdSoUYMsWbJw//597Ozs6NOnD2fPnqVw4cIsXryY7Nmzkzt37tQusqQDCTfHli1bxpYtW5g3bx7ff/89n332GWfOnKF79+5cv36dSpUqsWDBAnbt2sXWrVtTudQiIilLWU/k31PWk/REWU8skbJe+qaHcWJVHj16RKZMmShYsCBnz54lMDCQCRMm0K1bN5YvX87cuXM5efIkrVq1YsmSJdjY2CikibykcuXKjB07loMHD7Jo0SJMJhM7d+5k4sSJGI1Ghg8fTsuWLbG3t6dgwYLMmTOH+Pj4105xImLpnjx5wr1798iZMydXr15l8eLFdO3aFT8/P8LDw+nTpw+7du2iaNGizJ8/H1tbW+Lj41O72GLlTCYTcXFxHDt2jPbt21OqVCn+/PNP9uzZQ9u2bXF0dKR3797cvXuXihUrsmnTJnr06JHaxRYRSVHKeiL/nrKepCfKemKJlPXSNz2MkzQrYWSWyWQy/zk8PJxMmTIRGRnJDz/8QIECBahYsSINGzbE3d2d4OBg1qxZA7wYiZD41WARwXzDon79+nz33XccPHiQgIAAHj16RKVKlVi2bBm+vr6UKVOGHj16cOPGDX755RciIiIANGJSLNrr6qeTkxM1a9YkOjqa4OBgsmfPzieffEKlSpXIli0b4eHhLFy4MElbo6khJKUZDAYMBgOPHj3iyZMn3L9/n5UrV1KjRg369+9PpUqV+PPPP6levTrHjh2jSJEi2NnZERcXl9pFFxFJFsp6IslPWU+smbKepBXKeumbXWoXQOT/IvFCl1FRUcTExJApUyZatGhBtWrViI2NZc+ePXz77bd4eHhw6dIlypQpQ/369alVq5b5OBrdJfKXhPMqYSHvBg0aEBcXx5QpUzAYDLRq1YpixYrx8ccf8/HHH1O/fn1OnDjBnDlzWLJkCT169NA5JRYrcbtx7949nj59Ss6cOXnnnXcoUKAA8fHxrF27ljZt2pA7d27u379PtmzZGDhwIJUrVzbf1BNJCYnrZwJbW1vat29P9uzZuXjxIo8ePaJ+/foAeHh48Omnn1K8eHHKli1r3sfOTl17EUn7lPVEkp+ynlgzZT2xZMp6kpj+FSVNSriIzZw5k3379nHv3j3y58/PN998wzvvvMPp06e5efMmFSpUIDIykokTJ2Jvb0/t2rUxGAyvvRCKpGfR0dE4OjoCcOXKFZ4/f06JEiVo0qQJNjY2BAYGAtCmTRuKFCkCvFjYu2zZsri4uLB7924iIiJwc3NTSBOLlHgB771793L16lUKFy5MlSpV6NOnD0+ePCE2NhYXFxdu3LjBuHHjMJlMVKxYUe2GpKjEdWv79u3cvHmT2NhY3n33XT788EMABg8ezNOnTylfvjwABw8epFChQnTp0gWAuLg4hTMRsRrKeiLJS1lPrJ2ynlgqZT15mf4lJU1JfBFbvHgxCxYsoHv37tjb27N27VoGDhxIjx49qFq1Knny5KF69erkyZMHW1tb1q1bp0ZW5CXTp0+nW7du5nA2adIk1q9fz9OnT8mfPz+zZ8+mUaNGGAwGJk2ahMFgoG3bthQuXNh8DCcnJ65cuUJMTIzCmVicxNf8VatWsXbtWvz9/XFzc2PPnj3s2bOHBw8eEBAQQOHChRkyZAhZs2Ylc+bMrFy5EltbW7UbkmIST6E2ceJEVq1aRcmSJblw4QJbtmyhatWqDBkyhGzZsrF//37Gjh3LH3/8QWRkJDNmzDAfQ+FMRKyBsp5I8lLWE2unrCeWTFlPXsdg0nu4kgb99NNPnDhxgrx58/Lll1+aP+/UqRNXr15l/vz5ODg4sHv3bhwdHWnYsKF5fl1dxEReOHXqFM2aNeO9995j/vz5bN++nREjRjB48GAiIyNZtmwZUVFRLFy4kJw5c7J+/XqmTJlC6dKl6devH15eXjx48ID58+ezbds2Nm/eTJYsWVL7Z4m81k8//cQvv/yCm5sbHTt2BODp06esWbOG77//Hl9fXz799FP27duHg4MDlStXxtbWVu2GvBEXL16kb9++DB48mPLlyxMWFsbixYvZvHkzX331FV9//TVdunTBZDLh5uZGQEAA9vb2xMfHa10LEbE6ynoi/56ynqQnynpiyZT1JDE9jJM058yZM7Rr146wsDDGjBlDgwYNzNMuGI1GPvroIxo2bEivXr2S7KeLmEhS0dHR7N+/n2HDhlGwYEGqVKmCh4cHjRo1Al50GPr168ezZ89YtGgRb731FsuWLePgwYMEBQVhY2PD06dP2b17N6VKlaJgwYKp/ItEXmUymXj06BHvv/8+AO3atcPX19f8fWxsLK1btyZnzpxMnDgxyb5qN+RNmD17NkeOHCEuLo4ZM2aQMWNGAB4+fMj06dP5448/WLduHUajkbi4OBwcHABNVyIi1klZTyR5KOtJeqCsJ5ZOWU9epvdwxeK9/Lw4R44c9OzZk8yZM/PLL78A4OjoSExMDAAFCxbEaDS+chw1siJ/iY+Px9HRkQ8//JAhQ4Zw48YNpkyZQlxcHPDivCtcuDDjx4/H1dWV9u3bc/PmTVq0aMHMmTOxsbEhPj4eV1dX6tWrp3AmFiWhDUhYoD5btmxs2rSJzJkzc/z4cW7dumVuW+zt7SlRogTx8fGvHEfthrwJRYoU4ejRo/zxxx/cvXsXeFF3s2XLRsOGDfnzzz85efIkNjY25nCm6UpExFoo64kkP2U9sWbKepKWKOvJy/QwTiya0Wg0z0seHh5OZGQkmTJlonnz5nTr1o3du3czfvx4ABwcHDAYDDx9+tQ80kBEXmUymcwdz9DQUGrWrMmAAQPImTMnW7duBcBgMCQJaZGRkeaFvV8+htYOEEuSeM7/27dvc+fOHe7fv0+RIkVYtGgRFy9eZNKkSdy4cQOj0cjz5885ffo0OXPmTOWSS3rw8g3khLc8vv/+e+Li4li6dCmhoaHm66qjoyPFixd/ZVooXXdFxBoo64kkP2U9sWbKemLJlPXkv6FpKsViJYxyAQgKCuLXX3/lypUrlC1blsaNG/PBBx+wbNkyJk6cSLly5ciRIwcPHz7kypUrbN++XaMIRF4jcef1wIEDzJ07l549e1KhQgV2797NoEGDKFGiBAsWLAD+Og9v3rxJzpw5NXpM0ozJkyeza9cuwsLCAOjSpQstW7bkwoULNG3alCxZspA/f37gxRQRq1evNo9EE0kJifs127Zt4/bt24SGhlK3bl1KlCjBL7/8Qtu2balduzaff/452bNnZ/r06YSHh7N8+XItLC8iVkVZTyT5KetJeqGsJ5ZGWU/+W3oYJxYpcSdy0aJFzJw5k169enHv3j3Onz/PTz/9REBAAJ9//jnLli1j5syZGAwGxowZY54rWvM/iySV+Lzavn0727ZtY//+/bzzzjv06tWL8uXLExwczMCBAylZsiTz588HknYqdF6JpUpcT7dv386wYcMYNWoUJpOJ3377jXnz5vH111/Tr18/zp07R5s2bTAajfTq1Qtvb29sbGyIiYlRSJMUkbh+jh07li1btuDl5UV4eDjXrl3ju+++o2PHjhw9epT27dsTHx/Phx9+iL29PVOnTsXGxibJNVxEJC1T1hNJfsp6Ys2U9cSSKevJ/0LDycQiJVyALly4wB9//EH//v1p0KABAFevXmXhwoUMHz6cvHnz0rBhQ2xsbBg3bhy7d+82BzQRSSrhvAoICGDjxo3Uq1ePr776ioMHDzJz5kw6dOhAjRo1ABg8eDD169dn48aNSV6RVzgTS5VQT3ft2sXRo0dp166duT5/+umn5MiRg5EjR1KxYkWqV6/OkiVLaNasGXv37qVq1arkzZtX4UxSTEL9PH/+POfOnWP27Nm8/fbb2NraMnXqVCZNmkSWLFlo1KgRixcvpm3btri4uNCjRw9sbGwwmUwKZyJiNZT1RJKfsp5YM2U9sWTKevK/0L+0WKzDhw/TrFkzfvzxxyQXpfz589OiRQuyZs3KqVOncHZ2pnbt2vTr14/NmzfTt29fQB1JEYDHjx8n+fuZM2fYtWsXU6ZMoV+/fgwePJhRo0ZhZ2fH7NmzOXHiBDVq1GDgwIFkz579lTmvRSzZ5cuXWbJkCWvXrjUvUB8XF4fRaKRly5ZUr16dNWvWEBMTQ5EiRVixYgW///47fn5+XL16NZVLL9Zux44d+Pj48OjRI3LmzImdnR22trZ89913NG/enAkTJhASEkKFChWYO3cuP/zwAzNmzODSpUtaN0BErI6ynsi/p6wn6YmynlgyZT35b+lhnFichJlTq1atytdff01sbCzHjh0jNDTUvE2RIkVwcXHh2rVrAGTIkIEvv/ySnj17cvjwYUJCQtAMrJLe9enTh6FDhyb5zGQyERUVhbOzs/mzSpUq8fXXX/Pbb78RGBjIsWPHqF27NnPnzjW/Li9iyRLqaMGCBWnZsiXFixdny5Yt3L9/Hzs7O3N7kDFjRlxdXXFwcCA+Pp6iRYuyYMEC7t69i4uLS2r+BLFSCXXPZDLx5MkTHBwcuHfvHnZ2dubpcgDq1asHwL179wCoUqUKCxYsYOvWrSxcuJDY2NjU+QEiIslMWU8keSjrSXqhrCeWSllP/i/0ME5S3ciRI9m4cSOPHj0CXrzem3Ah6tatGx06dODQoUPs2LHDvDjr06dPAcibN6/5OG5ubjRp0oSdO3eSPXt2jSyQdK9Hjx6MHz8e+OuciYmJ4enTp+ZRlAmdg0qVKlGgQAFu377N4sWLOXfuHIBelxeL1KtXL2bMmEFwcDBAkjr6+eef07lzZzw8PBg0aBChoaHY2toSFxfHnTt3yJ49u3mf+Ph4SpYsye7du3nrrbdS5beI9Tl//ry5v5LQFzEYDDRp0oR27dqRNWtW+vXrR0REhHm6HAcHB7JkyWK+eWY0Gnn33XdZunQpX3/9Nfb29qnzY0RE/iVlPZGUoawn1kpZTyyZsp78WwaThpRJKlq/fj0DBgwAXnQQCxYsSNeuXXF1dU0ycmXcuHFs27aNYsWKUaBAAa5evcqtW7fYsGED9vb2SRbLFEnvFi1aRPny5SlVqhQAy5cvZ86cOaxevRoPDw/69OnDoUOHWL58OQULFgQgPDycfv36UaJECTZt2kTbtm1p2bJlav4Mkdfat28fnTt3pnjx4jx58oT8+fNTt25dPv30U1xdXc3bbd++ncWLF3P79m2KFCmCq6sr58+fZ+vWra90dtWGSHLp0aMHu3btokaNGpQvX54mTZrg5uZm/j4uLo6tW7eyZs0aHB0d6d27N1FRUcyePZvnz5+zZMkS8w0HLeItImmdsp5I8lPWE2umrCeWTFlPkoMexkmqunHjBqNHjyZ37tw8ffqUAwcOEBsbS6VKlWjRogVFixYlc+bMAEydOpWgoCCKFClC9erV6dWrF/DiYmdnZ5eKv0LEcpw6dQpvb2/q1KlDu3btKF68OGfOnKFXr164uLgwZ84cnj9/jr+/P7/99htdunTBwcGBAwcOEBYWxvr16/nuu++IjY1l+vTpqf1zRF6rVatWxMbG0rlzZyZPnsz169fx8PCgVatWlC5dmtKlSwNw4MABJk+ezK1bt/juu+/w9vYG1G5IykkIaK1bt2bNmjV4enpSuXJlOnbsSKZMmXBzcyMmJoadO3cydepUbt26xXvvvUeePHno168fzs7OCmYiYjWU9USSl7KepAfKemKplPUkOehfX1JVwqviN2/exMfHh/Xr1/PJJ59w8eJFvv76a/r168fs2bOJj4+nR48eDBgwwDzlQnh4OIAaWZFEypYty+TJk/nll1+YP38+586do3jx4kybNo3o6Gg6d+6Mo6Mj06dPx9vbm23btrF161YyZ87MihUrAIiPj+ftt99O5V8i8qr4+HgA6tatS3h4OBkyZGD16tX06tWLt99+m5EjR9K6dWtGjx7N4cOHqVatGl27dqVYsWKsWbMmyRRZIskpYWxb9+7dyZ8/Pzlz5mTdunUULFiQHTt20KBBAwYMGMD+/fuxt7fnyy+/pH///pQuXZqwsDB69eqFs7Mzz58/VzgTEauhrCeSvJT1xJop64mlUtaT5KQ34yTVJIwGuHDhAo0bN6Zbt2506tQJgBMnTtC6dWsyZMhAaGgoefLk4e2332by5MlMnTqVLVu2ULNmTTp06GCeE1okvUs8/cL27dsZO3YsFStWpEOHDhQrVozz58/Ts2dPnJycmDt3LtmzZycyMhJ4sZ6A0Whk2bJlLF++PMm0JiKW5tatWzRt2pTq1aszcuRI8+eVK1cmS5Ys3Lt3j6ioKAoWLMioUaMICQlhwYIFhISEsGzZMjw9PVOx9GLNQkND6du3LwALFiwgIiKCsLAwZsyYwYYNGwAoX748n376KdWrV+f48eMsXryYLFmyMGnSJPMbIiIiaZ2ynkjyUtaT9EJZTyyVsp4kBz2OlVSTMBogZ86cfPjhh2zZssU8AnLo0KFUrVqVmTNnMnXqVHLkyMHDhw+xs7Ojd+/efPLJJxw8eBBbW9vU/AkiFsVgMGAymYiLi6NWrVqMGDGCvXv3snDhQs6dO0eRIkWYMmUKMTExdOjQgfv37+Pm5sa9e/do1aoVbdu2Zfv27SxcuFDhTCyW0Wgkd+7cfP3116xbt46LFy8C8OWXX1K4cGHmz5/P2rVradeuHYUKFaJs2bJ8+umntGrVijx58pgXshdJCVmyZKFFixYcPnyYzZs34+7uTu7cuTl79ixVq1bl22+/5f79+4wdO5Y5c+ZQt25dOnbsyLVr1/Dz80Nj5ETEWijriSQvZT1JD5T1xJIp60ly0JtxYhF2795N9+7dGTNmDIsWLcLNzY2pU6eSNWtW8zYvL7oaGhpKlixZUqO4Ihbj+++/5/333ydfvnwAxMbGmhcs7tevHz/99BMGg8E8j3XRokU5f/48rVu3pnr16owdOxaA/fv3kzVrVjw8PPDw8EitnyPyX/v999/p3r07H3zwAceOHSNz5szMmDHD3C4kPhcSPH36NMnC3yLJzWQyERkZSdeuXbGxsWHMmDF06dIFd3d3pk2bRubMmQkNDeXixYu88847ODg4EBsbS3BwMCVLlsTLyyu1f4KISLJT1hP5v1HWk/RKWU8skbKeJAc9jBOL0bZtW44ePUqlSpWYMWMG7u7uwIt5oxNGRRqNRgDNsSsC/PHHHzRp0oQGDRrQtWvXJA179+7duXbtGmvWrOHQoUMMGzaMSpUqmUPajRs3yJUrl0YcS5o2ZMgQVq1axfvvv8+MGTNwdHQEXr2h9/LfRVLa3LlzCQwMxMXFhTJlyjBmzBg8PDxeqYsxMTE4ODikYklFRN4MZT2R/42ynqR3ynpiqZT15N9QL1csRrVq1bC1taVevXq4u7ubw1jiDqSNjY3Cmcj/V6pUKYKCgti0aRPTp0/n4cOHAPTo0YNr164RFBSEk5MTNWrUYNCgQRw/fpwJEyZw/fp18uTJg62trXmRZJG0JKF9aNSoETlz5sTT09MczuDVRbsVzuRNSRjj1q5dO8qUKYOTkxMBAQHmUegv10WFMxFJL5T1RP43ynqSXinriaVS1pPkoJ6upLiEhvTvJFzMWrZsSf78+dm+fTugEZEi/4nJZMJkMvHxxx8zffp0Nm3axNSpU+ncuTNXr15lzpw5eHl5mc+/zz77jO+++w4HB4ckoyo1WlIs0d+1Gwk3FBLah6JFi5I/f35+//13oqOj31j5JH1L6Lcknlwi4c8J67mYTCbKly9PVFQU586dA/65PyQikhYp64kkP2U9sWbKemLJlPUkpWmaSklRRqPR3JBev36dsLAwMmTIQMaMGcmcObP5Fd6E7ebNm0dgYCBLly6lXLlyqVx6EcuXcA7t2bOHb7/9Fjs7OxYtWkSFChXM38OrI3QSn5siliRx3Tx58iQhISE8e/aMatWqJVk7JmG7U6dO0axZMyZNmkStWrVSq9iSTiSun3FxccBfb3K8fF29ffs2DRs2pG7dugwaNChVyisikpKU9URSlrKeWBtlPbFkynryJtildgHEeplMJvOFasqUKQQHB/P48WNcXV3x8PBg4MCBFC1aFPhr5EuVKlU4cuQIZcqUSbVyi6QlCSNzPvnkE+bNm0eHDh3YsGEDnp6eeHl5/e2UDQpnYqkS6ubEiRPZs2cPJpMJFxcXBg0axIIFC6hUqVKS7Tw8POjQoQM1a9ZMtTJL+pA4gC1btoyTJ09y69YtsmfPjq+vL7lz506yba5cuahWrRqXLl0CtJ6FiFgXZT2RlKesJ9ZGWU8slbKevClqoSXFJFyE5s6dy6pVq/Dx8eHQoUNUqlSJ3377jcjISJ4/f27e3mg0UqJECebPn6/5zUX+BwkhLWFh43Xr1hEUFMTNmzdTu2gi/yfLli1jzZo1jBw5kh07dtC4cWPi4uIwGo3mdiNhGoicOXPSt29f7OzszKPXRFJCQjibMGECQUFBFClShPr163P06FG6dOlCWFgYkDTItW/fnvnz56damUVEUoqynsiboawn1kZZTyyRsp68KXoYJynGaDQSFRXFkSNH6N69O9WqVWP//v1s27aNESNGYGNjw+rVq4mJiQFeHb2l+c1F/nuJR00GBQWxefNmxowZw4MHD1K7aCL/0YYNGwgPDzf/PT4+njNnztCuXTvKlStHcHAw48ePZ9SoUWTKlAl/f3/Cw8NfO+LXzk4v/EvySuijJPjjjz8IDg5m6tSpdOzYEU9PT0wmE126dOHKlStERkaapzGBF2td2NraYjQaNVJSRKyKsp7Im6OsJ2mVsp5YMmU9SQ16GCfJKvEShEajEScnJ+7cuUO5cuU4fPgwvXr1om/fvtSrV49jx46xYMECIiIiUrHEIpbv5YVgY2NjX7tdQkj7+OOPCQgI4PHjx2TLlu1NFFHk/+Tnn3/Gz8+PmTNnEhkZCby4OXf//n0MBgN79+7Fx8cHHx8fGjVqxJ07dzhw4AA3btxI5ZJLetC9e3emTZtGVFSU+bNHjx4RFxdH+fLl2bNnD71796ZPnz7UqFGDuXPnMmfOHODVtVs0XZSIWANlPZHkp6wn1kpZTyyZsp6kFg0rkGSVcEFas2YNoaGhfPPNN2TIkIFevXpx//59/P39adiwIQDZs2cnW7Zs2Nvbp2aRRSxa4lfgly9fzqVLlzh58iQ1a9akcuXKlCtXLsn2BoMBo9FIrVq1zAscawFvsVSVK1dm7NixDBo0CJPJROfOncmUKRO5cuVi2bJlPH36FB8fH5o3bw5AhgwZyJw5M25ubqlcckkPihQpQlBQEG5ubrRq1QoXFxccHR3JnDkzixYtYsqUKfTv35+mTZvy/Plz7t+/T65cuYBXA5qIiDVQ1hNJXsp6Ys2U9cSSKetJalGLLckuLi6O3bt3s3//fgC6detGXFwc+fLlo2HDhhiNRmJiYti8eTM5c+bE3d09lUssYrkSglVAQABBQUFkzpyZDz74gKVLlzJixAiePHnyt/skjF5WOBNLlLBWTP369Rk6dCiLFi1i6dKlAPTs2RMXFxfc3NwoU6YMkZGRhIaGMnv2bHLlykWePHlSs+iSDsTHx9OtWzf69etHYGAg33//PdHR0RQrVoxHjx4xduxYunTpQtOmTYEXgcze3p633noLSPr2iIiINVHWE0k+ynpirZT1xJIp60lqMphUg+RfMplM5lEBCX++fPkyX331FcOGDePzzz9n2bJlzJ49mwwZMpAzZ04iIiKIjo5m3bp12NvbJzmGiCR19OhRBgwYwJQpUyhVqhQnTpygXbt2BAYGkjNnTjJlykSOHDlSu5gi/7XE1/xp06YRFhbGihUriI+Pp1WrVvTv359r167RsWNHjEYjJpOJbNmyYTQaWb16Nfb29hoFLCkmPj7evJbRhQsXCAoKIjg4mB49etCpUyfzOhfFihXj448/Jlu2bKxevZpHjx6xYcMGrWchIlZFWU8kZSnribVR1hNLpqwnqU01SP61xMEq4c+enp588sknHDhwgDp16tCoUSPKlStnblhz5MjB119/jZ2dHXFxcbqYiSTycsczIiKCLFmyUKpUKbZv387AgQPx8fGhQoUK9OzZk4YNG1K3bt1ULLHI/yahrZg3bx7Lli0jICCA999/n1u3bjF69GgABg4cyJYtW9i+fTthYWG89dZbfP7559ja2qrdkBSVEM7GjRtHcHAwxYsXp1ChQkyaNInY2Fi+/fZbFi9ezJAhQ5g3bx5Zs2bFy8uLuXPnYmdnlyTgiYikdcp6IslLWU+snbKeWDJlPUlturpJspg1axbnz5+nfv36fPjhh7i5uVGjRg169+5N8+bNKVu2LKVKlaJUqVJJ9ouPj1cjK/KShHC2f/9+KleubJ62ITg4GH9/f/r27UuLFi0AuHv3LufPn1dAkzQnPj6eY8eO0aJFCz744APz5zly5KBHjx7Y2dnRq1cvmjRp8sp+ajckpf30009s2rSJ2bNnU6JECQwGA8uXL2fEiBGYTCa6devG4sWLiYiIwGAwkDVrVgwGg24eiIhVUtYTST7KepIeKOuJJVPWk9Skd37l/yTx7KYxMTFkz56dc+fOMWbMGJo1a8axY8eoUqUK3t7eLFiwgKdPn752Tl2NJhB5vV9//RV/f3+uXbvGZ599hr29Pd26dcPHx8cczsLCwnB2diZ//vypXFqRf2Y0GpP8/dmzZ1y+fJnY2Fjz93FxcdSoUYPmzZuzaNEixo0bR2RkZJL91G5ISni5jxIWFkbmzJkpUKCA+bMWLVowaNAgZs6cyaJFi4iLiyN79uxky5YNg8GAyWRSOBMRq6CsJ5KylPXE2ijriSVT1hNLoodx8j8zGo1JpisxGo00atSITZs2MWTIEFxdXRkwYADdunXj7t27REREmEcTiMh/p0yZMri4uLBo0SJcXFzo0qULefPmZcuWLRw9epQffviBfv36AVCvXr1ULq3IP0sYBbx3714iIiJwd3fnk08+YdOmTfz555/Y2NiYt8mYMSPFixfn/PnzuLi4pGaxJR14eT0keNG3uXz5MiEhIdjY2BAXFwfAe++9h62tLWPHjiU4ODjJcdTPERFroKwnkvKU9cTaKOuJpVLWE0tjML1uCJvI30g8v/nixYv57bffOH36NFWrVqV69ep8+OGHAOzatYszZ86wePFioqKi6NmzJ126dEnNootYrJfXDUj4++7du5kwYQKTJk2iYMGCHDhwgHnz5nHu3Dny5MlD7ty5mTZtGvb29pq3WtKEEydO0Lt3b8qXL8+IESO4ffs2gwcPBmDQoEGUKFGCZ8+e0b17d+rWrUv9+vWBpB1okZSyevVqjh8/zqhRozAajbRp0wY7OztGjhxJ3rx5gRfTRU2bNo2KFStSt25djY4UEauirCeS/JT1JL1Q1hNLpqwnlkIP4+T/JDAwkNWrV9OoUSPi4+M5cOAA9vb2eHt707RpU/N2ly5d4siRI3h7e+siJvIP9u3bR+nSpcmQIQN2dnZcuXKFHj16ULduXb755htzcLt06RJZsmQhc+bMmrda0pSYmBjmzp1rXih5yJAhHDt2jJkzZ3Ly5EkKFChgHpG/fv167O3tFc7kjYiJiWH8+PH89NNPfPDBB/j5+fHjjz8yY8YM80LeBoOBNWvWEBkZyYoVK3T9FRGrpawnkvyU9cTaKeuJpVLWE0uih3HyP/v999/x9fVlzJgxlC1bFoAzZ84wc+ZM7t+/j7+/P6VKlXplBJguYiJ/7/z589SrV4/ChQtTtmxZunXrhqenJ2vXrmX8+PEsX76cQoUKAUlHjr18nolYisR1M3GdjY2NZf78+Wzbto0yZcowePBgoqOj2bt3Lw8ePCBLlix8+eWX2NnZqd2QFPO6a2dkZCRz585l9+7dfPjhh/j6+nL06FG+//57Dh48SIECBciWLRtBQUG6eSAiVktZTyT5KeuJtVHWE0umrCeWTFc9+Z+Fh4cTGxtLrly5iI+Px8bGhuLFi9OlSxdatWrF2bNnKVWq1CsXPjWyIn95uXNQpEgRDh06xMqVK9m/fz+1atXC29ubQoUK8fHHH3P48GEKFSr0yn4KZ2JpDh06xPvvv2+um2vWrOHu3bt07doVOzs77O3t+frrrzEajaxbt46RI0fi6+vLl19+meQ48fHxajckxSTUz9OnT1OyZEkA3Nzc6NixIyaTybxGgI+PD++++y43b94kS5YsuLi4aJSkiFg1ZT2Rf09ZT6yVsp6kBcp6YsnUsst/ZDQaX/ns2bNn3Lp1i/DwcGxtbYmLi8NkMlG8eHG8vLy4d+9eKpRUJO1IHLKOHTvGrl272Lp1KwaDgW7durFmzRq++eYbrl69yvjx49m4cSOrVq0CFMjEsm3ZsoUOHTqY62t0dDR79uxh165dLFq0iPj4eAAcHBzo2rUrJUqUYP369fTp04dnz54lOZbWxZDk1rNnTzZu3Gj++86dO+nVqxdLly41f+bm5kaHDh2oWrUq69atY8KECcTFxeHl5YWrqysGgwGj0ahwJiJWQVlPJPkp64m1UtYTS6asJ2mFapf8rcSdyGvXruHo6IinpycfffQRpUuXZvDgwYwZM4Y8efIAEBERgcFgMP9dRF4v4bwKCAhgy5YtuLi4cPPmTQoXLky9evVo164dnTp1IiQkhJs3bzJ58mRsbGw0TYlYvOrVq9O5c2eGDx9OfHw8zZs3Z9y4cYwaNYotW7ZgNBpp164d9vb2AJQsWZKIiAiKFSuGk5NTKpderNmzZ8+ws7PD398fJycnPv/8c0qVKkWhQoXYvHkzNjY2tGjRAoAMGTLQpk0btm3bxubNm8mUKROdOnUyH0vXYRGxBsp6IilDWU+slbKeWCplPUlLtGac/KPAwEDWrFmDq6sr5cuXZ/To0ezbt4+pU6diNBrp3LkzcXFxbNmyhYcPH7J27VqNchH5B6tXryYoKIjJkydTqFAhQkJCmDp1KleuXKFly5Y0adLEPEd1ZGRkklE66hyIJXv69Clz5sxhzpw5DBw4kJYtWxIWFsaIESO4ePEidevWpXXr1tjb29OrVy/KlStHmzZtAK2LISkrLCyMKVOmsHr1asaNG0ft2rW5d+8ew4cP5969ezRs2JCWLVsCL25MBwYG8sUXX1CzZk3VSxGxWsp6IslPWU+slbKeWCplPUkr9DBOXpF4kcpdu3YxYsQIfHx8OHv2LAcOHKBgwYJMmTKFn3/+mYULF3Lo0CHefvtt3nrrLaZMmYK9vT3x8fEKaSL/wYABA3B1dWXgwIHm8+Xq1asMHjwYR0dHZs2ahZ2dXZLzUQvIiqV6OVjFxMQwY8aMV0La8OHD+eOPP3B0dMTBwYFnz56xZcuWV+q6SHJKXD/Dw8OZOHEia9euZdy4cdSpU4e7d+8ycuRI7t69S7Vq1ahZsyaTJ0/GxcWFwMBA3RwTEauirCeS8pT1xJoo64klU9aTtEYP4ySJxBegZ8+e8eOPP/Lw4UPatm1LdHQ0mzZtYt68eRQtWpTAwEBsbW25cuUK2bNnx83NTQtdivwDo9FIbGwsjRs3pnLlygwaNAij0YjJZMLW1pbg4GC6devGjh07yJ8/f2oXV+QfvbwuRkhICDly5CBv3rx8//33zJw5k0GDBtGiRQsiIiJYv349ly9fxsXFhb59+2JnZ6ebepJiEtdPk8lEbGwsMTExBAYGsnLlSsaPH0/t2rW5e/cuEyZM4MiRI9jY2JAzZ06WLVuGvb29wpmIWA1lPZGUpawn1kZZTyyZsp6kRepFi5nJZDJfgObMmcOJEyf4+eefqVu3LnFxcTg6OlK3bl0AFixYQLdu3Zg6dSoFChQwH0MLXYok9XLDbmNjg6OjI++99x5bt26lQYMGlChRAqPRaN6mZMmSZM2aNTWKK/I/S6jfEyZMYOvWrTg6OpIlSxaGDBlC+/btiYuLY+TIkZhMJlq2bEnr1q2TjIrUTT1JKYmvvwsXLuSPP/7gypUr+Pr60qlTJ+Lj4/H19cVkMlGnTh2GDBnCvXv3CA8Pp1y5ctjY2Kh+iojVUNYTSX7KemLtlPXEUinrSVqlGidA0ovY3LlzmT17NrVr1yZfvnzs3buXunXrUq5cOZydnfnyyy8xGAwEBAQQGBhIv379zMfRaAKRvyS+6bFs2TKuXbtGxowZadu2LU2aNOHkyZOMGDECf39/SpQoQVhYGKtXryZ79uy4u7unculF/nvr169n48aNTJs2jaJFi/Lw4UO8vLwAaNq0KS4uLowdO5aYmBi+/vrrJPuq8yspJeH6m7AeUps2bciSJQsRERF4enrSt29f7O3t6d+/PzY2NtSqVYsMGTKY94+Pj1f9FBGroKwnkvyU9SS9UNYTS6SsJ2mVap0Af13Ebty4wZUrV5g5cyaVKlUiMjKSrl274uPjw4QJE3jnnXdwcnKiTp06ZMmShY8++ih1Cy5iwRJGhAUGBrJixQry5MnDo0ePOHHiBEFBQfTq1Ytp06bRtGlT8ubNi8FgwM7OjjVr1mjeakkTEub+//3333nvvfd45513AMzhbOfOnfzxxx907tyZBw8eEBwcTLt27bRegLwx586dIzg4mMmTJ1OpUqUk3124cIEmTZpgMpno3bs3WbJk4d133zV/r+l0RMRaKOuJJD9lPbF2ynpi6ZT1JC1Syy9mwcHBNG/enP3795unUXBzc2PGjBnkyZMHHx8fTp06RXx8PM7OznzyySfY2toSHx+fyiUXsSyJpyGJiYnh3r17zJs3j+XLl9O3b19CQkLo0qULZcuWZdasWQwbNow6derQoUMH1q1bh729PXFxcQpnkmaEhYURGRn5yuc3btxg1apVxMfH079/f5YtW4bBYEDL1cqbEh0dTWhoKM7OzubPYmNjuXr1Kr179yY0NJTvvvsOHx8fKlSokIolFRFJWcp6IslDWU/SG2U9sVTKepIWqfVPx15uIGvUqMHHH39MaGgoBw4c4MmTJwC4u7sTFBREvnz5aNOmDRcvXkyyn0YTiPwl8QjHgwcPsmbNGs6dO4e9vT0ODg589tlndOzYkYcPH/LNN99gMplo1KgRXbp0oX79+uabHnpdXixR4psP8NeI4CJFinDo0CGOHTuW5PsSJUpQpEgR7OzscHBwMIczjZaUlPBy/QR49uwZRqPR3KcBsLe3J3/+/Dg6OnLu3DlcXV1p3749dnZ2xMXFvcESi4ikHGU9keSnrCfWTFlPLJmynlgLPYxLp4xGY5IGMioqCoDhw4fTtGlTtm7dyvr16wkLCwNejJqcMmUKzZo1o3DhwqlSZpG0ICGcjRs3jm7durF48WLOnz/PtWvXiI2Nxc7Ojlq1atGpUyciIyPx9vZ+ZZSZbnqIJUp882H9+vVMnjyZ6dOnA9C5c2cqVapEr169OHToEHfv3iU8PJxFixbh7u6Oq6ur+TgKZ5ISEtfP+/fvc/v2bQCqVKlCyZIlGTp0KJcvXzZvHxkZScaMGfHw8EhyHN0cExFroKwnkjKU9cRaKeuJJVPWE2tiMOn94XQn8UVs5cqVHD9+nMuXL1OyZEnat29P3rx5GThwIEeOHKFly5Y0atSIjBkzJjlGfHy8OpEiiSQeAfbrr78yZswYBgwYgLu7O7Nnz+bQoUMEBARQtWpV7O3tiY+PZ/369Rw/fpxRo0bpfBKLlrh+jx07llWrVpEnTx6uXLlC2bJlmTlzJrGxsQwZMoSDBw+SMWNGMmbMiK2tLatWrcLe3l6jJOWNmDp1Ktu2bSMyMpIPPviAsWPHcv/+fXr27MmNGzdo164drq6u7Nu3j5CQENauXavrr4hYFWU9keSnrCfWTFlP0gplPbEGehiXjgUEBLBlyxbq169P/vz58fPzo0qVKsyYMQMXFxcGDhzIzz//TL169WjXrh1ubm6pXWQRi7d+/XouXrzI06dPGT58OPBiLYE+ffrw888/ExAQwHvvvYednV2SmyW66SFpwY0bN+jXrx9Dhw4lR44cXLt2jV69epEnTx5mzpxp7vg+e/YMW1tbatSoga2tLXFxcRqFJiki8XV00aJFBAUF0aVLF8LCwli+fDnvvvsuEydOxGQyMXToUM6dO4etrS158uRh7Nix5htmuv6KiLVR1hNJfsp6Ys2U9cTSKOuJNdLDuHQk8UiVkydP0rdvX8aNG0eFChX49ddf6dChAxMnTsTDw4PixYtjZ2dH165dsbOzY8qUKRrlIvJfGDBgAOvXr6dw4cIsWLCA7NmzAy9CWt++ffn1118ZPnw4H3/8sToEYtFOnTpFqVKlzPV01apVbNiwgYwZMzJp0iTzdCTHjx+nT58+5MqVizlz5iSZpgR080HejF9++YVff/2Vt99+m08//RSTycTBgwfp27cvFStWZMaMGcCLBejt7OxwcXHBYDDo5oGIWA1lPZGUp6wn1kJZT9ISZT2xJlozLh2IjY0Fks7d/OjRIzJmzEiFChXYvXs3nTp1wtfXl48//pjx48ezYMECAIKCgpg8ebJ5IVYR+cvrFpAdPXo0Xbt25f79+yxbtowHDx4A4ODgwIQJEyhcuDCrVq1Sh1Us2qJFi2jWrBl79uwhPj6euLg4YmNjefDgAdevXzeHMJPJRPny5Zk0aRL37t3jq6++4unTp0mOpbouyc3Pz499+/aZ+yW///473bp1Y+bMmea+jsFg4P333ycgIIBjx47RrVs3YmJiyJgxI66uruZ+jcKZiKR1ynoiKUNZT6yVsp5YMmU9sXZ6GGflJk6cSPfu3WndujU7d+4kIiICAGdnZ6Kiopg/fz6+vr7069eP5s2bExsbS1RUFI8fPzYfw8bG5pVFwEXSu8Svy584cYKDBw+yfv16TCYTPXr0oFmzZqxbt47Vq1cTEhICvAhp8+fPZ86cOalZdJF/1LZtW+rXr4+fnx/BwcHY2dlRv359unbtyr179+jXrx/w142/cuXKMXr0aPLnz4+Tk1NqFl2snMlk4uLFiwwaNIijR48CkDt3brp06YKzszOHDx82b2tjY8MHH3zAhAkTCA4ONo+YTKB+jYikdcp6IilDWU+smbKeWCplPUkP9IjYirVq1YpHjx5RqFAhbt++jZ+fH2PHjuWzzz4jR44cODk5ERgYSMeOHfH29gYwjx7IlStXkmMldERF5IWEc2LSpEkEBwdjMBgICwtj9uzZDBkyhN69exMbG8vq1asxGAw0btwYT09P7O3tgaQBT8RSzJkzh2zZstGwYUNGjRqFyWSif//+mEwmPv/8c2rXro3JZGLEiBHY2toyZswY4EWnuXLlylSuXBnQdCWSMnbs2MEXX3zB999/T69evejduzcTJ06katWqNGrUCKPRyIQJE3B2dsbHxwd4ca1+7733WLVqFSVLlkzlXyAiknyU9URSjrKeWCNlPbFkynqSXuhhnJXy9vYmOjqaFStWkCFDBgwGAw0bNuT777/ns88+o2DBgrRt25aAgADOnj3LmjVryJgxIytXrsRoNNKsWbPU/gkiFm/RokWsWrWKOXPmUKZMGTZs2ICfnx+Ojo7Ex8fj6+uLyWRixowZ5MiRg0aNGpn3VTgTS/T06VOcnZ0BkgQwPz8/AD7//HPq1KkDwMiRI7GxsWHUqFGvjDpTOJPkdu3aNXbu3MkXX3xhvsHcq1cv+vTpw6RJk6hSpQpNmzYFICAgABsbG/r06QO8uN6WKVMGQOsGiIhVUNYTSXnKemJtlPXEUinrSXqiHoIVat68OdHR0Xz//fdkzJjRvI5AhQoVyJYtm3m7evXq0bt3b+Lj4xk2bBizZs3CwcGBNWvWYGdnR3x8fGr9BJE04cKFC3Tu3JkyZcqwY8cORo0axfDhw7Gzs2PkyJEA9O/fnwEDBlC/fv3ULazIf6FMmTJs3bqVW7duAS86tmPGjKFmzZr4+fmxc+dOnJ2dqVu3LoMGDWLdunXMmjUrlUst6YGNjQ0nTpzgzJkzwIsp2KZMmULp0qXp3bs3hw8fxs3NjaZNm+Lj48PChQsZOnToK8dROBORtE5ZT+TNUNYTa6OsJ5ZKWU/SE9VSK9OmTRseP37Mtm3bsLGxISYmBgcHBwBu3bpFzpw5iY2NNU+f0LBhQ+rWrcu9e/dwdXUlc+bMGAwGjSYQSeTIkSM8fPiQUqVK4eHhgYuLC9HR0Zw6dYpChQpx7NgxBgwYQL9+/fjqq684cuQIa9asoUGDBpQuXZqWLVsCms5BLF++fPnM87Tnzp3b3BYkHjVpMBj47LPPqF27NlmzZqVatWqpXGpJD/LkycMnn3zC3r17KVKkCABOTk5MmTKFnj170qdPH/M0Jk2bNuXZs2ccOXIEk8mk9QJExGoo64kkP2U9SS+U9cRSKetJemIwmUym1C6EJI+QkBA6depEREQEy5Ytw9PT0/ydn58fGzZsoEyZMtjY2ODu7o6XlxfVqlXD1dWVChUqmLfV/OYif+nSpQunT58mJCQEZ2dnOnbsSOvWrXFzcyMwMJAff/yRmzdvMnDgQJo0aQLAjz/+SEBAAEuWLCF79uyp/AtE/jf9+/fn+PHjbNu2DQcHB3NIMxqNDBgwgODgYPz9/alXr555H93Ukzdhzpw5rFq1ii1btuDi4mKud9HR0fTs2ZPffvvNPI1JVFQUTk5O5vWRFNJEJK1T1hNJfsp6kt4o64mlUtaT9EK9cCvxww8/kD17diZOnEjWrFlp0aIF9+/fB6B79+4cO3aMdu3aUa1aNXLlysXdu3fZsWMH33zzDZMnTybxM1mFM5EXvL29CQkJITAwkB07dlC3bl3mzp3Lo0ePAHj33XeJiIigcOHCvP322wCEhoayevVq8uTJk2SqIBFLZzQaAfj2229xdnbG19eX2NhY7OzsiIuLw8bGhtGjR1OxYkU2bNiQZF+FM3kTOnXqhLOzM3379gUw101HR0emTJnCO++8Q7t27fjjjz9wdnZWOBMRq6GsJ5L8lPUkPVHWE0unrCfphd6MswLXrl1j0qRJTJ06FaPRyNWrV+nfvz/h4eHkzp2bhw8fMmvWLN566y3zPk+fPiUmJoZTp05RrVo1Tacg8hJvb2+io6NZunQprq6uADx69IhPPvmE0aNHU6tWLQB2795NYGAgkZGRODs74+joiI2NDWvWrMHe3l6jjyXNiY2NZdWqVaxevZpSpUoxbNgw89oytra25iCnei1vUkLQ2rZtG9OnT6datWrmxeYTRk1GRUUxbdo0+vTpo36NiFgNZT2R5KesJ+mVsp5YImU9SU/0MM4K3LhxgxYtWjB79myKFy8OwJUrVxg1ahQ//fQTS5YsoVKlSkka15cbVr12LvKXFi1aEB8fz/z583F1dTWvxxESEkLHjh0ZPnw4pUuXNncYTp8+zZUrV7h27Rr58uWjdu3a2Nra6rySNCehTj979ozFixezfft2PDw8CAgIIEuWLEm2Vf2W1BAeHs78+fPZs2cPFSpUeO3C3aD6KSLWQ1lPJHkp60l6pawnlk5ZT9IDPYyzEkOHDiV79ux888035gvSpUuXGDRoEKGhocydO5e8efOmcilFLN/ixYsZM2YM33//PRUqVDCHMwB/f3/Wr19PYGAgBoOBrFmzUrRoURwdHV8ZmaMFvMVSve4mXeLpHRL+HBUVxd69e1mwYAF37tyhU6dOlCtXjtKlS6dGsUXMdfPx48esXLmSjRs3kjlzZkaOHImnpyfu7u7mbTRSXUSsibKeSPJQ1hNrp6wnaZWynqQXehhnJV5e6DLhApUwjUloaCjz5s1TSBP5B3fu3GHIkCGcPXuW6dOnU7ZsWQB69uzJjz/+SK5cuYiLi+PWrVsAZM+eHQcHB/z8/KhRo0YqllzknyXutF6/fp3o6GjzGhiJJQ5sRqORoKAgrl69yk8//cQnn3xCnjx5+Oabb95o2cX6Ja6ffzf/f+IRvefOnSMwMJDQ0FAKFChA48aNyZ49u/nNERERa6GsJ5I8lPXEminriSVT1hN5QQ/jrEidOnXIkycPQUFBST6/evUqfn5+nD9/np07d+Lp6ZlKJRSxXHPmzMHDw4P69etz69Ythg4dytmzZ1m6dCnTp0/n4sWLjBs3jgIFChAZGUlkZCQnT57kt99+IyQkhClTpug1eUkzAgMD2bJlCw8fPuT999/Hz88PLy+vf9zv4sWLhIWFkStXriRr04j8W4nD2aZNm7h27RpZsmShadOm5hHrCV4Ob/v27ePChQscPnyYzJkzM2jQILJmzfpGyy8iktKU9UT+75T1JD1R1hNLo6wn8hc9jLMC/2mhy4TvLl68yJIlSxg6dKimUxB5jcDAQLJly0arVq0AuH37NoMHD+ann34iV65crFq1imzZsgF/Pz+15q0WS5W487ts2TKmTp1Knz59MJlMzJo1i9y5czN69OjXhrSEduTvRq+J/FuJ69a4ceNYuXIlefPm5dy5c3zyyScMHjz4tTeXX54i6vnz59jY2LwS6ERE0jJlPZF/T1lPrJmynlgyZT2RpPQwzor8twtdan5zkVf9+OOPzJ49mwkTJpg7qTdv3mTy5MkcPHiQpUuXUqRIkST7JHR6Ey6j6ryKpTty5AjXr1/Hzc2NOnXqAC9GQHbo0IE8efL8bUgTeRPu3r1L586dGTVqFHnz5uXy5ct06tSJChUqMGTIEL3tISLpmrKeyP+dsp6kB8p6YsmU9URe0GqHVsJkMpEhQwbatm1L7dq1OXLkCM2aNePSpUtERESYtwF1IkVeJ1++fJhMJi5dugS8OF+8vLzo3bs3pUqVol27dpw+fTrJPgmjzwwGg84rsXiXL1+mXbt2DB06lPDwcPPnhQsXZt68edy8eZNBgwZx9erVVCylpFezZ89m2LBhFChQgLfffht3d3fKli3LzJkzOXbsGMOHD+f+/fupXUwRkVShrCfy7yjribVT1hNLpqwn8hc9jEsjjEaj+c+ve5kx4bXyzJkz06ZNG8aMGYO9vT09e/ZkwIAB7N+/n7NnzwJ/dSpF5C8FChSgQIECjB49mpiYGPM5lStXLkaMGEHx4sXp3Lkzp06dSu2iivxXXm4rvLy8CAwMJGvWrPz888/ExMSYt0sIaceOHWPp0qWpUVxJx+Li4nB2dubo0aOcP3+e2NhY4EXdLF++PLNmzeL48eP07t2b0NDQVC6tiEjyU9YTSVnKemJtlPUkrVDWE0lK01SmAVroUiRlJZxjN2/e5Ntvv6VgwYKMHz8ee3t78zl1584dunfvTrZs2Zg9e3ZqF1nkP0rcbkRGRppH9Lq4uLBt2zYGDhxIrVq1GDVqVJI1Am7dusVbb72l6a0kRSWunwni4+NZv349w4YNo0WLFq+sh/Tzzz8zZ84c5s6dqxvNImJVlPVEUpaynlgbZT2xZMp6Iv+ZHsZZOC10KfLmxMbGsmrVKlavXk2pUqUYNmxYkkW6Q0JCyJo1qzoHYtESd37nzJnDsWPHuHTpEjlz5qRdu3Z88sknbNu2jQEDBlC3bl1GjBjxytQ7Wm9GUkri+nns2DHu37+Pra0tJUuWJHfu3KxYsYKRI0fStm1bfHx8gFdvPr8u4ImIpEXKeiJvjrKeWANlPbFkynoi/8zunzeR1JRwQbp79y6HDx9m6dKlSRa6HDZs2GsXuny5YXVycnpjZRZJi0wmE/b29jRs2JCIiAi2b9/ON998Q0BAAFmyZAEge/bswIsgZ29vn5rFFflbCR3XwMBAVq5cSY8ePShdujQXL17k22+/ZcyYMTRo0AAAf39/wsPDmTp1apJjKJxJSkmonwEBAezYsQN4MXXJ06dPCQgIwNvbG5PJxOjRo7GxsaFPnz6v3EBQOBMRa6GsJ/JmKOuJtVDWE0umrCfyz/QwLg2YPXs2J0+eNC906eDgYF7oskuXLgwfPvxvR02KyF9eN8ImYRROwvQNLi4utG3blrx587JgwQLq1KlDp06dKFeuHKVLlwZQOBOL8/DhQ7Jly2b+++XLlzlw4ACTJ0+mSpUqAISGhpIzZ04GDhxI3rx5qV27NtHR0WzatEmjz+SNWrVqFZs2bWLy5MkUKlSIu3fvsnjxYnr06MGCBQto3rw5NjY2DB06lLfeeovmzZundpFFRFKMsp5I8lDWE2ulrCdpibKeyH+mq7GF00KXIskjcQf0+vXrXLhwASDJKJyEkObs7EytWrVYvXo1zZs3548//qBTp04MHDhQawiIxfnmm2+YNm1aks/Cw8O5d+8eGTJkMH+WJUsWWrVqRdGiRdmzZw8AdevWZfHixdjY2GA0Gt9ouSV9mDJlCo8fPwZe9F1MJhO//fYbDRo0oEKFCmTKlIlixYrx3XffUa1aNUaMGEF4eDgNGzZk+vTpfPXVV6n8C0REUo6ynkjyUNYTa6WsJ5ZMWU/kf6eHcRbm5QbSzs6OFi1aMHDgQG7cuGF+vTyhI1muXDmmTJmCk5MTmTJlSoUSi6QNiadzaNeuHY0bN6Zr167cvHkzyXaJA5uNjQ3dunVj4sSJLF26lAYNGvDll1++0XKL/JN+/foxcOBAACIiIgCIjo4mLi6O8PBw4K+2JWfOnDg7OxMVFQUkHfmr0ZKS3E6fPs3hw4dxd3cHMI9Mv3HjBk+ePEmyraenJ9WrV+fBgweEh4fj4OBAjRo1sLOzIy4uLhVKLyKS/JT1RFKGsp5YK2U9sVTKeiL/N5qm0oL8p4UumzRpQlxcHCNHjsTOzg4fHx9zSKtcuTKVK1d+5RgikvScWLZsGStXrqRPnz6YTCZmzZrFgAEDGD16NF5eXq/smzCticlkonDhwm+66CL/lYIFCwKwaNEitm3bxvTp03n33XcpUqQII0aMYPbs2eb6HRkZiclkIn/+/KlZZEknSpYsycqVKzEYDOzevZvSpUvj6elJ7ty5OXr0KHfv3uWtt94yb5/w3cvTQ9nZqbsqImmfsp5I8lPWE2unrCeWSllP5P/GYDKZTKldCEnq7xa6/Pjjj1m+fDmjR4+mXbt29OnTJ5VLKpJ2HDlyhOvXr+Pm5kadOnUAuHjxIh06dCBPnjx/G9JELFXCDYQEv//+Ox06dKBkyZKMGzeOiIgI+vTpQ2hoKM2bN8fFxYW9e/fy8OFD1q9fr06vvDG3bt2iRo0a1KhRg/HjxxMVFUWzZs3w8PBg+PDhZMuWDYPBwHfffYeDgwNBQUGvLOQtImItlPVEkp+ynlgbZT1JK5T1RP43ehhnYVatWsW0adNeWehy69atLFiwgEqVKrFy5UqGDh3K4MGDtdClyH/h8uXL1K5dG+CV8+bixYt07NiRvHnzMnToUI0ikzTh5ZHxUVFRODs7c+bMGTp06ECxYsUYPnw4jo6OjB49mj///BN3d3fy5cvHmDFjsLe3Jz4+Hltb21T8FWKtXvfmxqFDh/juu++oWrUq/v7+3Lp1C19fX8LDw3F3d8fNzY34+HjWrl2Lvb293v4QEaukrCeS/JT1xNoo64klU9YT+Xf0MC4VTZkyhdatW5M5c2YS/hkGDhxI1qxZk4yEvH//PsOGDePmzZssW7YMJycnDhw4wEcffaTRLiKv8fIospiYGPbs2cPIkSOpUKECAQEBODg4mLe7dOkS9erVo2nTpgwePDgVSy7yz16ejuf48eM8fvwYf39/ChQowJkzZ2jfvj1FixZlwoQJZM2alSdPnmBvb4+LiwsGg4G4uDi1H5IiEtfPc+fOERUVRaZMmcifPz9Hjhyha9eufPzxx/j7++Pi4sKKFSuIjo4ma9as1K9fH1tbW9VPEbEKynoiKUNZT6yZsp5YMmU9kX9Pj6FTiRa6FEkZRqPRHM4iIyN5+vQpcXFxfPHFFwwYMID9+/czdOjQJGsEFCpUiB9++OH/sXfX0VFd/duHPxM3IHgIFiw4FGkpUigUihZtiwX74cW9wd3drcWLB3dK0UKx4h6kBEiwIIF45v2DN/MkJEhLQibhvtZitcyR2Wc4M3Pu2fvsr6kwsog5i7z4HTt2LDNnzsTJyYlSpUqRPn16APLly8cvv/zC1atX6dmzJ7dv38bZ2RlHR0fTOa+LX4kPRqPRdH5OmjSJDh060KlTJ7Zv3054eDglS5Zk+vTp7Nmzh4EDBxISEkKzZs1o06YN9erVw9LSkvDwcJ2fIpLoKeuJxA9lPUnqlPXEXCnricQNvQMSiApdisS9qKN05s6dy/Hjx7l27Rqurq60aNHCNH1J3759sbCwYNiwYaYwlylTJgBN5yCJwv79+9m2bRvz5s0jX758+Pr6cvLkSTZu3EiRIkVo1KgRc+fOpW7duixZsoS+ffuattX87BJfIs+tGTNmsHr1aiZPnoyjoyOZM2cmLCwMX19fSpcuzaxZs+jYsSOdOnVi4sSJprtGDAaDPn9FJElQ1hOJe8p68qlQ1hNzpKwnEjd0Z1wCMhgM+Pj40KlTJ4YNG8bLly/p1asXAD179sTb25unT5/y7NkzFi1aRLp06UiXLl0Ct1rEfEUdpfPLL79Qrlw56tatS+rUqenQoQPr1q2jevXqjBw5kq1bt9KlS5cY+9DFgSQGL168IEeOHKbpIAYPHsygQYO4evUqQ4cOZfXq1eTLl4/t27fTp0+fhG6ufEICAgL4+++/6du3L1988QU2NjYsXbqUqlWrUrVqVRYsWMCXX37J+PHjAUiRIgWgHw5EJOlR1hOJW8p68qlQ1hNzpawn8uE01O4je71IZaZMmZg/fz7dunXD09OTAQMGMG7cOPr06YOHh0eMQpcGg0GFLkWiePjwIWnSpDH93dvbm/379zN58mRKliwJwOPHj3F1daVfv35kzZqV6tWrExwczIYNG/R+ErMX2zmaIkUKDh48SIsWLTh16hQ1atSgZ8+eVKtWjZYtW3Ljxg0A3NzcAI0Clo8nODgYb29vzp8/z5MnT1i4cCEuLi7UqFEDo9HIxIkTqVatGl9//TVff/01EPs5LiKSGCnricQtZT1J6pT1JDFR1hP5cOqM+4jeVOiyTJkyTJ06lZ9++olRo0YxYMAANm3apEKXIu/Qtm1bXFxcGDJkiOmxZ8+e4evrS/LkyU2PpUqViiZNmvDXX3/x+++/U7RoUb777jvq1q0L6OJAzFfUc/P8+fP4+vqSN29eSpUqxYwZMzhz5gw//fQTZcuWNW3z9OnTGCPrFc4kPrz+2RkREUHq1Klp2LAhv/76K0ajkQYNGvDNN99QqFAh9u/fz4kTJ7C3t4+2H33+ikhSoKwnEreU9SSpU9YTc6asJxI/dKX/kbxe6HLz5s0EBwfTuHFj2rRpYyp02bFjR0JDQxk5ciTNmjWLtg8VuhSJrnfv3mTOnBmA58+fkyxZMoKDgwkLC+PZs2fA/y4gXF1dsbe3JzAwECBaTQ5dHIg5ivq9MX78eLZs2cLLly+pU6cOPXr04JtvvuGbb77h+vXr7N+/H4Bly5YRHByMh4dHQjZdPgFRw9myZcs4d+4cPj4+zJgxgzZt2lC5cmVSpkxp+rHMaDSyePFikiVLRrJkyRKy6SIicU5ZTyTuKetJUqasJ+ZMWU8k/uhq/yNRoUuRuJcjRw4AFi5cyJYtW5g+fTpffvkluXPnZtiwYcyZM8cU4AICAjAajWTLli0hmyzy3iK/N+bNm8f69euZMGECbm5u2Nvb8/LlS548eUKyZMnw9vame/fuZM+enXTp0uHl5YWVlZWmK5F4FRnOxowZg5eXF1WqVKFYsWIYjUYAsmbNip+fH3379iU8PJyHDx8SEhKiadhEJElS1hOJe8p6kpQp64k5U9YTiT8GY+Q7SeJdQEAAXbt2pXbt2tSoUYOrV6+ya9cu1qxZw8OHD+nWrRstWrRg7969LFq0iF9++UUfXiKxiPzRItKZM2do1aoVBQoUYMyYMTx//pwePXrw+PFjGjVqhIODA3/88QcPHz40XbyKJAaBgYF07dqVsmXL0rhxYy5cuMCOHTtYu3YtAQEBNG7cmF69euHt7U3y5MlJkyYNBoNB01zJR7F7925GjhzJvHnzyJEjB/7+/ly9epVt27ZRrFgxPvvsM/bu3cv58+fJmjUrrVq1wsrKSueniCRJynoicUNZTz4VynpizpT1ROKHOuM+okePHvH9999TpUoVMmbMaCp0WbRoUYxGIwsXLmT37t2kT5/etI1GE4hE9/p7IjAwEHt7ey5cuECrVq3ImzcvQ4cOxdbWlpEjR3L+/HmSJUuGm5sbo0aNwtraWqPIJFEwGo0EBQXRsWNHUqVKRY4cOVi5ciWZM2emXLlyBAYGMnv2bLZv306mTJlM2+l7Qz6Wbdu2sXbtWqZMmcLFixdZsGAB586dw2g08vz5c8aOHUulSpWibaPPXxFJqpT1RD6csp58KpT1xNwp64nED3VVxxMVuhSJe6/PW33ixAn8/f0ZMGAA+fLlY/78+bRs2ZL+/fszfvx4Jk6cyJMnT7C2tsbBwUGjyMSsvf69YTAYsLe3p0yZMqxfv579+/fTpEkTKlasSJ48ebh27Rr79+/n9TE1+t6Q+PD6KHWA4OBgzp07R8uWLTl16hTVq1enT58+VKtWjbp163LmzJkYAU3hTESSAmU9kbinrCdJmbKemDNlPZGPR3fGxYO3FbpMnjw5t27dilHosnXr1lhaWjJ79uwYH4AiEt3YsWPZsGED33zzDZkzZ6ZRo0Y4OjoCcOHCBdq0aUOuXLkYOnSoqY4AxH6BIWIOon5v7NixAz8/P65fv853333HZ599RmhoKEaj0VRDwM7OjtatW2M0Gvnll190Xku8inp+vnz5kufPn5vu7NiwYQPXr1+nSJEilCxZEltbW0JDQ2natCk1a9akYcOGCdl0EZE4p6wnEr+U9SSpUdYTc6asJ/JxqTMuHkUtdJkyZUpatGhBihQpAPDz82PYgff8PAABAABJREFUsGExCl1aW1vrtnORt9i/fz+DBg1ixowZ5MuXD19fX65evcrGjRspUqQIjRo14sKFC9StW5emTZvSt2/fhG6yyHsbN24cW7dupWDBgty/f5/Lly9Tr149evfuzaNHj5g4cSL37t0jKCiIsLAwVq9ere8NiVdRf9iaO3cuBw8e5PLly2TPnp3y5cvTrFkzbG1t8fHx4Z9//sFoNLJkyRLu3LnDunXrNDpdRJIsZT2RuKesJ0mZsp6YG2U9kY9P75p4snv3bnbs2MFvv/1mKnR5+fLlaIUuv/zyS86fP0/hwoVV6FLkPb148YIcOXKQLVs2Dh8+zKJFi7hy5QrJkydn06ZNWFtb88MPP7B9+/ZoIyVFzN2mTZvYsGED8+bNI2/evBw+fJhWrVpRoUIFHj58iKurK4ULFyZt2rSkTp2aZs2a6XtD4l1kOJsyZQqrV6+mW7duFC1alM6dO7Ns2TLKly9Pzpw5OXDgANOnTydFihRkzJgRLy8vrKysVDdARJIkZT2R+KGsJ0mVsp6YI2U9kY9Pn+jxJDQ0lOzZs+Pi4sLx48ejFbpcv349Y8eOxcPDI9o24eHh+pIViSK2EWApUqTg4MGDtGjRglOnTlGjRg169uxJtWrVaNmyJTdu3ADAzc0NUAFZMV+vn98+Pj6UKFGCvHnzsnnzZgYOHEjfvn1xcXFh8ODBDB48WN8b8tEZjUZ8fHz4/fffGT58OF9//TXHjx/Hx8eHUaNG8fTpU/7++28aNmxIgQIFSJ06NS4uLlhYWOjHAxFJspT1RD6csp4kZcp6khgo64l8fLrPOQ7ENtNn1EKXHh4e2NnZ0adPH/bv30+2bNk4c+ZMjG10ESnyP1EvXs+fP8/vv//O3bt3KVWqFDNmzKBEiRLMnTuX8ePHU61aNQCePn1KunTpou1H7ysxV5Hn9969ewG4ffs2oaGhnDlzhoEDB9KzZ08aN25MqlSp+PPPPzl27FiMfej8lvgQERFh+n+DwYDBYCAgIICvv/6aPXv20Lp1a3r27EmVKlVYsmQJ8+bNA6BgwYK4urpiYWFBRESEwpmIJAnKeiJxT1lPkjplPTFXynoiCUvvnA/0pkKXtWvXxmAwcP36ddq1axet0KWtrS2urq4J3HIR82U0Gk3vq/Hjx7NlyxZevnxJnTp16NGjB9988w3ffPMN169fZ//+/QAsW7aM4ODgGKPJRMxN1O+NGTNmsHDhQtauXUv16tXp0qULO3fuZNSoUdSpUweAx48fkzlzZk3FIx9F1M/fCRMmkCpVKurUqUNgYCCenp7s3LmTPn360KBBAwBSpUqFr69vjP2oroWIJAXKeiJxT1lPkjJlPTFnynoiCU+dcR8g6ofYuwpdnjhxwlToMiAggB9++CGBWy9iviLnrZ43bx7r169nwoQJuLm5YW9vz8uXL3ny5AnJkiXD29ub7t27kz17dtKlS6d5qyVRiPze2LlzJ8+ePWPmzJlkyZIFOzs7qlSpwp9//snDhw959uwZ9+7dY8qUKaRIkYLChQsncMvlUxD5+Xvy5Ek2b97MqFGjsLe3p1atWqxatYqKFSuawpnRaOTSpUsUKlQoIZssIhIvlPVE4oeyniRlynpizpT1RBKeOuM+gApdisSfwMBAjh8/Tvv27SlRogQXLlxgx44drF27loCAABo3bkyvXr1Yv349yZMnJ02aNBgMBs1bLWbLaDSavje8vb3p3Lkz8Gq6B4B06dLRvHlz7OzsmDNnDjNmzCB9+vSkTp2aJUuWYGlpqe8N+Sjmzp3L9u3bKV++PF9++SUANWvW5N69e/z555/0798fZ2dnTp8+TUBAAL169UrgFouIxD1lPZH4o6wnSY2yniQWynoiCctgjG0SfHkvkYUuO3ToQPfu3U2FLlu3bs2oUaNIkyYNFhYWFC1alLNnz6rQpch7MhqNBAUF0bFjR1KlSkWOHDlYuXIlmTNnply5cgQGBjJ79my2b99OpkyZTNvFVgRcxBxEDWd+fn6kT5+e7du3M3z4cIoUKcKYMWNwcHAAICAggCdPnnDhwgVcXFwoUKCAvjckXkU9PwGWLl3KhAkTyJo1K4sWLSJFihQAXL16lf3797NmzRoyZsyIq6srAwcO1I/OIpIkKeuJxA9lPUlqlPXEnCnriZgXfdL/S1EvAGMrdNmjRw9TocsuXboQEhLCrFmzTKNhIvehL1mR/3k9WBkMBuzt7SlTpgzr169n//79NGnShIoVK5InTx6uXbvG/v37eX0sgcKZmKOo5/ehQ4cYM2YMY8eOpUqVKhiNRvr27cvQoUMZOXIkFhYWODo64uTkFO3Hh/DwcH1vSLyIGs42b95M7ty58fDwwN7enkGDBjF16lQGDBgAQK5cuciVKxdNmzbF2tratA/9eCAiSYWynkjcU9aTpExZT8yZsp6I+dG76V9QoUuRuBf14nXHjh34+flx/fp1vvvuO5o2bUrDhg0xGo2mGgIRERGMGjUqxgWsiDmKen5v2rSJP/74gytXrjBixAg8PT2pWrUqAJ6enhgMBkaMGBHrd4RGoUl8iHp+nj59miVLluDo6MjQoUOpV68eYWFhDB06FBsbG/r06WPaJmoYMxqNCmcikiQo64nEPWU9ScqU9cScKeuJmCe9o/4FFboUiXuRFwfjxo1j69atFCxYkPv377Nhwwbq1atH7969efToEQMHDuTevXsEBQURFhbG6tWrMRgMmq5EzFrkuTlmzBg2b95MjRo1qFmzJufPn2fkyJH07t3bFNL69evH06dPmTFjRrRpJETiQ9QfnadNm8bRo0fx9fXl/v37DBo0iH79+lG/fn0Ahg0bhsFgoHfv3jE+b3WuikhSoawnEveU9SQpU9YTc6WsJ2K+1Bn3L6nQpUjc27RpExs2bGDevHnkzZuXw4cP06pVKypUqMDDhw9xdXWlcOHCpE2bltSpU9OsWTOsrKx0u7wkCmfPnuX3339n0qRJFC9eHID9+/ezevVqxowZw4ABA6hatSrBwcGsW7cuxpzuIvEh8hxbtGgRixcvZvz48WTNmpU///yT3bt3M2LECAYMGED9+vUxGAwMHDgQV1dXPDw8ErjlIiLxR1lPJO4p60lSpqwn5khZT8R86crmHV7/onRwcODGjRtERETw9OlTUqRIQb58+ejYsWO0QpfZsmVToUuRN3h9hKOPjw8lSpQgb968bN68mYEDB9K3b19cXFwYPHgwgwcPjnFRoHnVJbEIDQ3l+fPnODk5mR4rW7YsYWFheHp6MnToUAYMGEDt2rWpWbMmFhYWGgUs8c5oNBIeHs7x48dp3Lgx5cqVA8DNzY106dIxa9Yshg8fzuDBg/nxxx9JlSqVaR0RkaRCWU8k7inryadEWU/MkbKeiPnSp/9bvF7o8urVq3h4eNC/f3+uXbvG1KlTTevmypWLli1bsnHjRubPn8/QoUNNo7kUzkSii7zw3Lt3LwC3b98mNDSUM2fOMHDgQHr27Enjxo1JlSoVf/75J8eOHYuxD72vxBxFFpo3Go1EREQArwKawWDA398fePXjAkCFChVwdXXl/v37jB8/Hm9vbywsLKJNKSESXwwGA1ZWVgQEBPD06VPgf+dvxYoV+eKLLzh48CDDhg3j5s2bVKxYEWtra8LCwhKy2SIicUZZTyR+KOtJUqWsJ4mFsp6I+dI3wBtERESYwllkoctRo0bh4+NDvXr1GDBgACtWrGDMmDHRtlGhS5E3i7xgBZgxYwa9evXin3/+oXr16vz555/8+OOPDBgwgEaNGgHw+PFjMmfOTObMmROqySLvLer3RkREBC9fvgSgRIkSFCxYkEGDBnHz5k3TjwuPHz8mTZo0VK9enSdPnnDixAlA87JL/Ij6+RtV5syZOXDgAPfu3Yt27mXLlo38+fMTHBzMggULCAwMBNB1jYgkCcp6InFPWU+SMmU9MWfKeiKJhzrjYvF6ocvx48fj6+vL4cOHGTRoENevX6d+/foMHDiQJUuWMHbsWODVCLCoH276khWJLvJ9tXPnTp49e8bMmTPJkiULuXLlokqVKri6uvLw4UOePXvG5cuXGT9+PClSpKBw4cIJ3HKRt4s61cjChQv56aefqFGjBq1atWLXrl307t0bZ2dnmjZtyrx581i5ciXdu3fn+fPndOvWDWdnZ/76668EPgpJqqKen8ePH2ffvn2sX7+e4OBgunfvjr29Pd26dePatWs8e/aMoKAgdu/eTfny5SlTpgx79+7l+fPnCXwUIiJxQ1lPJH4o60lSpawn5kxZTyRxMRgj71OVGBYtWsT06dNjFLo0GAwMGDAANzc3Vq1axcCBA+nfv78KXYq8QdRpgLy9valevToA48ePp0aNGgBcu3aNFStWsH79esLCwkifPj2pU6dm0aJFWFtbqx6HJAoTJ05k3bp1tGzZkkKFCtG+fXtcXV2ZNm0aKVKkYNSoUVy6dImwsDDc3NwYN24ctra2dOvWDXd3d9q3b5/QhyBJ2MSJE9mxYwf29vbcu3ePlClT0rFjR3LkyEHv3r3x9/cnWbJk2NjYEBQUxI4dO7h+/TqdOnVizpw5ZMqUKaEPQUQkzijricQNZT35VCjriTlT1hNJHHT/aSxU6FIk7kQNZ35+fuTIkYPJkyczfPhwduzYQYUKFXBwcCBnzpx07dqV5s2bc+HCBVxcXChQoAAWFhaEhYXpdnkxe9euXWPnzp2MHTuWkiVLcuLECYKDg2nXrh1+fn5YWFgwcuRIXrx4QVBQEFZWVrx48YI5c+bw559/0qlTp4Q+BEnClixZwurVq5kzZw6FChVi3bp1eHp6kjFjRrJnz87GjRtZtWoVwcHB2NjY8MMPPwCwcuVKnJycSJEiRQIfgYhI3FDWE4k7ynryqVDWE3OmrCeSeGiaylio0KVI3Ig6r/qhQ4do3bo1ly5dokqVKvTr14+DBw8ydOhQ0/zWjo6OZMqUiW+//ZZChQphYWFBeHi4wpmYnadPnxIYGEjUm8ufP39OREQEJUuWZPfu3bRq1YpevXpRuXJlZs6cyezZs4FX5/ndu3dp164dHh4ebNmyhQULFpA9e/aEOhxJwiI/X69cuYKHhweFChVi69atjBgxgsGDBwMwevRoDAYD9evXp2nTpmTPnp0lS5bg6emJl5cXQ4YMIVmyZAl4FCIicUdZTyRuKOtJUqWsJ4mFsp5I4qPOOFToUiQ+RJ23etOmTaxdu5YrV64wYsQILly4QNWqVRk5ciTbt2+nX79+0cJcVJquRMzNsGHDaNeuHXXq1GHWrFncvXsXgOTJkxMUFMTYsWPp06cPffr0oXHjxgDY2dkRHBxs2kfBggVp2rQpI0aMYPHixeTLly9BjkWSngMHDrB+/XouXrxIQEAAFhYWBAcHc+rUKRwdHTlz5gz9+vWjR48eNGjQgPDwcJYvX87Zs2dN+zh06BA7d+7k5cuX/Pbbb+TJkycBj0hE5MMo64nEPWU9SaqU9cScKeuJJH6ffKJ4vdDlixcv8Pf3p2rVqnTv3p2///6bbt26MXz4cNKlS4eNjY2p0KWdnR1LliyhQ4cO2NvbJ/CRiJiXyPfVmDFj2Lx5MzVq1KBmzZqcP3+ekSNH0rt3b6pWrQpAv379ePr0KTNmzIg1pImYCw8PD54+fUqpUqW4fv06s2bNwsLCgjZt2pAyZUoKFy7M0qVL+eGHH2jQoAHw6nvmwYMH5M2bF8BUEyPy/BeJK+3bt+fixYv4+vri4OBA/fr1+emnn0iWLBlVq1Zl4cKFjB8/nqFDh1K3bl0AXr58Sfbs2UmXLp1pP926dQMgNDQUa2vrBDkWEZG4oKwnEj+U9SQpUtYTc6asJ5I0fPKdcZEXka8Xupw9ezYdO3Zk7Nix9O7dm+bNm0crdDl37lyuX7/OunXrCAkJSeCjEDFPZ8+e5ffff2fSpEkUL14cgP3797N69WrGjBnDgAEDqFq1KsHBwaxbty5azQERc9OwYUOCg4NZvnw5Tk5OAHTq1AkvLy+aN29OqlSpaNy4MX5+fhw7dozJkyeTMmVK9uzZQ2BgIO3atQM0AljiR8OGDQkLC2PixIm4uroyffp01q5dS+3atcmdOzdFixZl165dODs7ky1bNgAePXrE8uXLcXV1JW3atED0H64VzkQksVPWE4k/ynqSlCjriTlT1hNJOj75zjhQoUuR+BIaGsrz589NF7MAZcuWJSwsDE9PT4YOHcqAAQOoXbs2NWvWxMLCItrFgYi58PDwICQkhKVLl+Lg4EBgYCD29vZ88cUXvHz50nTOfvnll3Tr1o1du3axcuVKsmXLhqurK/Pnz8fKyso0UlIkLkX+eLBkyRIcHR0B6N27Nxs3buTixYvkzp2bL7/8kjZt2rB48WJatWpFmjRpsLa2xtramlWrVunzV0SSLGU9kfihrCdJhbKemDNlPZGk5ZPujIv8IHpXoctBgwZRv359AI4ePcqSJUu4fPkyu3fvZsmSJSp0KQKmkY5GoxGj0YiFhQWhoaEYDAb8/f2B/03ZUKFCBVxdXbl//z7jx4+nb9++5MiRw7SdiDlp1qwZt27dYtu2bTg4OBASEmKarur48eM4OTkRFBSEhYUFVlZWlCxZkpIlS9KtWzdsbW2xsbEBICwsTPVmJM41bdqU0NBQli9fjq2tLSEhIdjY2BAWFkauXLnInDmzad2qVauSPXt2vL29uXXrFpkzZ6Zq1apYWlrq/BSRJEdZTyTuKOtJUqWsJ+ZMWU8k6fmk3okHDhzg0aNH5M6dm8yZM+Pk5GQqdFmvXj1TocvevXvToEEDjh8/zvLly6lbty4FCxYEXhW6PHbsGGnTpuW3334jV65cCXxUIgkv6gibiIgIAgMDcXJyokSJEhQsWJBBgwYxd+5c3NzcAHj8+DFp0qShbNmyHDx4kBMnTpAjRw5NWyJmJzQ0lBQpUhAUFMSpU6coXrw4dnZ2wKvRaDt27CBz5sw0atQIo9FIxowZKVWqFKlSpaJKlSqmcGY0GnXxK3Fu4cKFHD16lHnz5mFra0t4eLjpnJs4cSLnz5/H19eXHTt2kDx5cooWLUq2bNnInTt3tP2Eh4fr/BSRRE9ZTyR+KOtJUqWsJ+ZMWU8kaTIYjUZjQjfiY3hbocuZM2eyatUqHj58GK3Q5f79+xk9ejQLFiwgffr00fanQpcir0QNZwsXLuTw4cNcvnyZnDlzUr9+fbJnz46npye+vr40adKE5MmTs23bNoKCglixYgUtW7bE2dmZCRMmJPCRiMQuLCyM3r17s2/fPqZOnUrp0qXp3LkzV65coUGDBjg5OeHr68u5c+fw8fHh2rVrFCxYkFWrVulHB4lXz58/p2vXrnh7ezNy5EhKlSoFQJcuXdi/fz/p06fHysqKa9euAeDs7IyVlRWDBg2iUqVKCdl0EZE4pawnEj+U9SSpU9YTc6WsJ5I0fRJd4yp0KRJ/It8TEydOZN26dbRs2ZK2bdvSvn17Hj16xLRp0/jll18YNWoU27ZtIywsDDc3N+bMmQNA8uTJyZkzZ0IegshbWVlZMXbsWHr27Em3bt3Ili0bgYGBLFq0KNqPd5HT9pw/f558+fKZpvJRSJP4kixZMqZOnUqnTp3w9PRkxowZzJ07l5s3b7J06VKyZ89OcHAw/v7+eHt7c+TIEfz9/SlfvnxCN11EJM4o64nEH2U9SeqU9cRcKeuJJE1J/s642ApdPnv2jDJlyjB06FBq164NwLZt21i8eDFXrlyJUejS2tpahS5F3uLatWt07NiRQYMGUbJkSU6cOEHLli0ZM2YMadKkIUOGDLi6uvLixQuCgoJMxY2XLl3KsmXLWL58OdmzZ0/owxB5q7CwMAYNGsTatWsZNmwYP/zwg2lZREQEQLTvCRXwlo/lxYsXdOzYkcOHD5MxY0YWLlxoqh/wpvoAqhsgIkmBsp5I/FPWk0+Bsp6YK2U9kaQlSb8zVehSJO49ffoUGxsb7OzsTKPAnj9/TkREBCVLlmT37t306tWLXr16UblyZVq2bEnGjBkZOnQojo6OXL9+nZEjR/L06VPCw8NZsGCBwpmYndjCVeSUD0FBQYwdO5bUqVNTrlw5LC0tY/0BT+FMPhZHR0emTZtGv379+Ouvv3jw4AGZMmXCYDCYrl9eH7mr6xoRSeyU9UTinrKefAqU9SQxUdYTSVqS7J1xCxcuZPTo0cybN4+vvvoq2pdt//79WbNmDRMmTMDKyspU6NJgMJiKYUbSaBeR/xk2bBgXLlzA39+fmjVrUrt2bVxdXfH29qZFixbUqFGDlStX0qtXLxo0aABAhw4dcHJyYsyYMab9bNu2DRcXF1xdXWPU6BBJKOfPn+fChQvRRkHGJiwsjF69enHo0CHGjh1L2bJlNZpePop33bkROWry2rVrTJw4keLFi2vqHBFJkpT1ROKesp4kZcp6Yu6U9UQ+DUm2M06FLkXiloeHB0+fPqVUqVJcv36dI0eO0KFDB9q0acOTJ08YNGgQ+/bt44cffmDAgAHAq4uJBg0aULZsWTp27KgfPMSs/f3333To0IHmzZtjNBopWbIkBQsWjPUCNywsjD59+rBlyxaWLVtGsWLFEqDF8imJOtrx1KlTuLm54ezsHGO9Fy9e0LlzZ7y9vRkxYgSlS5f+yC0VEYl/ynoicUtZT5I6ZT0xZ8p6Ip+OJNsZB68+pDp16oS3t3e0QpejRo16Y6HLMWPG6HZekddE1uNYvHgxTk5OAHTq1InLly+zceNG7OzsOHLkCBMnTiQoKIgKFSqQMmVK9uzZw+PHj1m3bp3eV2L2/Pz8WLNmDb/++isvXrxg3759pE+f/o0j1EJDQ5k1axY//fSTzm+JV1HPwSlTpvD7778zZ84cMmTIEOv6L168oEmTJqRPn55Zs2Z9zKaKiHw0ynoicUNZTz4FynpirpT1RD4tSbozDlToUuRDeXh4EBgYyJIlS3BwcCAwMBB7e3uWLFnC3r17mTVrlmnKn8OHD7Nr1y62bdtGtmzZcHV1ZdSoUVhbW2ukpCQKCxcuZPz48Tg5OdGsWTPat28PvHvKCH1vyMfw119/MW3aNNq0aUPZsmXfum5QUBA2NjaaVkdEkjRlPZEPo6wnnxJlPTFnynoin4Yk/22iQpci/12zZs24desW27Ztw8HBgZCQEOzt7QE4fvw4Tk5OBAUFYWFhgZWVFSVLlqRkyZJ069YNW1tbU3DTxauYq9eDV+HChVmyZAmHDh1i2bJlBAcH07VrVywsLN4a0nR+S3w7dOgQQ4YM4dGjR6RIkQJ4+w8HdnZ271xHRCSxU9YT+e+U9SSpU9aTxEJZT+TTkWTesREREW9c5uTkxMiRI8mbNy9dunTh+PHjRL0hUAUvRWIKDQ0lRYoUBAUFcerUKdPIG4DevXuzY8cOLly4QKNGjahVqxZt2rRh4cKFbNy4MVo4MxqNungVsxT1wvX48eNs3rwZBwcHihQpwvfff0+9evVYs2YNU6ZMAcDCwoLw8PCEbLJ8Ql6fuKB06dJUrVoVo9HIL7/8wsOHD7GwsIix3usUzkQkKVDWE4lbynqS1CnriTlT1hP5dCWJaSpV6FIkfoSFhdG7d2/27dvH1KlTKV26NJ07d+bKlSs0aNAAJycnfH19OXfuHD4+Ply7do2CBQuyatUq/fAhZi3q98a4cePYvHkz4eHhVKpUCU9PT2xsbPDz8+O3335j9erVVK5cmcDAQGrVqkXJkiUTuPWS1EX98eDBgwcEBQWZpl2bNGkS27dvp1y5crRr145UqVLFuOtDRCQpUdYTiR/KepJUKeuJOVPWE/m0JfrOOBW6FIlfYWFh9OzZkz///JNs2bIRGBjIvHnzSJ8+vWkdo9GI0Wjk/Pnz5MuXD0tLS10wSKKwcOFC5s+fz+TJkylYsCBBQUGEhITg6+tLtmzZTOts2rQJa2tr1q9fr9G/Eq+iXtfMmDGD3bt34+vrS+3atenTpw/w6keFvXv3UqZMGdq2bauQJiJJlrKeSPxS1pOkTFlPzI2ynogk+s64SCp0KRJ/wsLCGDRoEGvXrmXYsGH88MMPpmWR0wZFfT+pgLckBqGhofTo0YNChQrRqlUrzp49y5YtW9i4cSOBgYFUqFCBoUOHYm1tzYsXL0iRIoVp+hKd3xLfxo8fz+rVq2nZsiUGg4EJEybQtm1bunXrZlq+b98+ChQogKenJ8mTJ0/gFouIxB9lPZH4o6wnSZGynpgzZT2RT1eSGPKhQpcicSe2i08rKysGDRpEUFAQY8eOJXXq1JQrVw5LS8tY30O6eJXEwNLSEltbWw4cOMDz589Zu3Yt7u7utGvXDktLS8aNG0fbtm1xd3c31cWIiIjQ+S3x7vDhw+zcuZN58+ZRqFAhDh48iMFgYM6cOTx79oxBgwbRs2dPXr58ydOnT3FyckroJouIxBtlPZG4o6wnnwplPTFXynoin7ZEmU5U6FIkbp0/f57Vq1cDbw5XNjY2jBkzhjJlyvDzzz9z4MAB00hJEXMX27lqYWHB119/jaWlJevXr6dZs2b079+fpk2b8s0335A9e/YY2+l7Qz6GmzdvkipVKgoVKsSlS5dYuHAh/fv3Z/z48SxfvpwpU6bg5+fHwIEDGT9+PBYWFvo8FpEkQ1lPJG4p60lSp6wniYmynsinLdHdGfemQpeRt/Ju376duXPnqtClyL8QEhLCpEmT8Pf3x2g0UrJkSQoWLBjjvWNlZcW4cePo06cP7dq1Y9myZRQrViyBWi3yfqJ+b2zYsIE7d+5w9epVKlWqxNdff0316tUJDQ3F2tqax48fExISQr9+/XB0dMTd3T2BWy9JXWzXKcmSJcPe3h4/Pz82bdpEjhw5qFy5Mo8fPwZg1qxZ+Pv7M3jwYAwGA0ajUT8eiEiSoKwnEveU9SQpU9YTc6asJyKvS1Sdce8qdNmtWzfCwsLYu3cvBoNBhS5F3pOrqyuNGzdmzpw5vHjxgtq1a2MwGGKd3sfKyorRo0eTNWtWChcunEAtFnl/kefw2LFj2bRpE+XLlycoKIgBAwZQqlQpJkyYwJMnT5g6dSqnT5/G2toagJUrV5pGoeniV+JD1HMrLCzMNOKxRo0a5M2bF3g1PVu3bt1IkyYNT548oXr16jRp0oSCBQua9qNrHBFJCpT1ROKHsp4kZcp6Yq6U9UQkNomqMy7yQyy2Qpc2NjZ069aNXr16YTAY2LdvH8+ePVOhS5H3kD59ehwdHQkODsbZ2RkvLy/at2//xotTa2trOnfuDLy6qLCySlQfJfIJ2rVrF1u2bGH27Nnkz5+fQ4cOcejQIerVq8fdu3dxc3OjdOnSZMmSheTJk/PDDz9gaWmp81viTdTP1sWLF3Pu3DmuXr1KtmzZaN26NXnz5uXo0aPcuXOHlClTAq+uf8LCwihcuDAGg0EF5kUkSVHWE4kfynqS1CnriblR1hORN0l03zoqdCkSN14PXoULF2bJkiUcOnSIZcuWERwcTNeuXd85WkwXr2KOXj9nfX19yZUrF/nz52fLli0MGDCAPn36kCtXLoYMGULHjh2pWrVqtH2Eh4fr/JZ4E/VHZy8vL9q1a0fBggX55ZdfaN68Obt27SJ9+vS4uLjQoUMHnJycsLGxYc2aNabpShTORCSpUdYTiRvKepKUKeuJuVPWE5E3SXTfPG8qdJkiRQp69uyJs7MzDRo0YODAgaYpS3TbuUh0Ud8Tx48fN1285s6dmwwZMhAaGmq6COjSpQsWFhYalSOJSuT5vW3bNipVqoSfnx9Go5Hjx48zYMAAevbsSaNGjQgICODYsWOcPXuWQoUKRduHzneJb2fOnOH3339n+vTpFC1alP379/PixQsGDRrE9evXcXd3Z8iQIVy+fJmgoCCaNGmClZWVRvGKSJKlrCfy4ZT1JKlT1pPEQFlPRGJj1u9uFboUiXtR3xPjxo1j8+bNhIeHU6lSJTw9PXFxcaFRo0bAq3nUnzx5QmBgILVq1aJkyZIJ2XSRd4r648OsWbOYNWsWefPmpUaNGixbtgwPDw/Gjx9PjRo1AAgICCBTpkxkzpw5IZstn6gXL14QFhZG0aJF2b17N7169aJnz55UrFiRnj17kjt3bjp16kTRokVN22gUr4gkFcp6InFPWU+SMmU9SUyU9UQkNmb7DlehS5H4EfmeWLhwIRs2bGDy5MkULFiQoKAgnj59iq+vr2kea2trazZt2oS1tTXDhw9P4JaLvFvk98b27dt5+PAhc+bMwc3NjRcvXtCyZUuWLl3K+fPnKViwIE+ePGHWrFnY2tpSunTpBG65JHWx/egcHByMnZ0dy5YtY8KECfTu3ZuGDRtiNBq5f/8+qVKlirEfjeIVkaRAWU8kfijrSVKmrCfmSllPRN6XWXbGqdClSPwKDQ3l5MmTNG/enOLFi3P27Fm2bNnCxo0bCQwMpEKFCgwdOpQ2bdrQuHFjUqRIoelLJNHw8/Oje/fuREREkDlzZkqWLImjoyN169bFzs6OefPm8dtvv+Hi4kL69OlZvnw5lpaWOr8l3kS9rvHz8yMsLIyMGTNStmxZJk6cyLBhw+jTpw8NGzYEICgoCEtLS7JmzZqQzRYRiRfKeiLxS1lPkjJlPTE3ynoi8m8YjEajMaEb8SZRC10aDAZ++eUXAgMD2bVrF/7+/nTs2JEnT55EK3RpbW0d64gEEfmfiIgI+vTpw/379/nss89Yu3Yt7u7ufP3111haWjJu3DhWrVqFu7t7tG00DZCYo8jP/Kif/WfOnKFLly64uroyYsQI3NzcgFej758/f86lS5dInTo1OXPmxMLCQvOyy0cxdepUtm/fzv3796lVqxY9e/bk6tWr9OrVC0dHR77//nvs7e3ZtGkTDx8+xMvLS+eliCRZynoi8UNZT5ISZT1JLJT1ROR9mG1n3JkzZ+jTpw8jRowwFbrs0aMHgwYNIlOmTLi7u3Pp0iUVuhR5hzcFqy1btrB27Vq8vb3x8PDgm2++IXv27Pj6+vLTTz8xcuRI8uTJkwAtFnl/Uc/vR48emcJW2rRpOXXqFO3ataNQoUIMGTKEDBkyvHMfInHFaDQSERFhGoE7b9485s+fT5s2bQgICGDhwoVUrlyZnj178uzZMwYNGoSPjw/Ozs5kzZqVcePGYW1trVG8IpIkKeuJxA1lPUnKlPXEXCnrich/ZbadcYcPH2bgwIHs2rUrWqHLevXqRSt0GZU+xESii3rhuWHDBu7cucPVq1epVKkS5cqVw9HRkdDQUKytrXn8+DFOTk60b9+ekJAQFi1apItWMWtRR0fOnDmTgwcP4uPjg52dHS1atKBhw4acOXOG1q1bU6RIEQYPHoyLi0sCt1o+BY8fP45WA+DChQscPXqULFmyUKFCBQD27dtH586d+fbbbxk+fDi2trbcv38fa2trnJ2dMRgM+tFZRJIsZT2RD6esJ0mZsp6YK2U9EfkQZvGuV6FLkfgRGbDGjh3Lpk2bKF++PEFBQQwYMIBSpUoxYcIEnjx5wtSpUzl9+jTW1tYArFy5EgsLC40iE7MV9dycNm0ay5Ytw9PTk6CgIK5du8bQoUN5+PAhnTp1Yvbs2fz000907dqVmTNnxvr9IRJXPD09SZYsGX379gXg5MmTNGrUyDQtVKRy5coxdepUunbtatouXbp0puVGo1HhTESSBGU9kfihrCdJlbKemCtlPRH5UAl+5RUREWEKZ35+fty5cweAsmXLYjAYGDZsGJ06dVKhS5H/aNeuXWzZsoXZs2czdOhQPDw8CA0NpV69ety9e5d06dJRunRpvvvuO3788UdWr16NtbU1YWFhCmdidn777TdCQkJM5+bdu3c5dOgQo0aNolatWtSvX59+/frx888/M2PGDHbv3k2RIkWYOnUqyZIlw9nZOWEPQJK8MmXK0KtXLwBevHhB0aJF+fnnn7G2tub8+fPR1o0MaZs2bWL58uXRlqkekogkBcp6IvFLWU+SEmU9MXfKeiLyoRK8Gz7ySza2QpfDhw+nV69ebNq0CVtbW1OhyxcvXtCsWbMEbrmIeXp9hKOvry+5cuUif/78bNmyhQEDBtCnTx9y5crFkCFD6NixI1WrVo22j/DwcI3SEbNTv359nJyc+PHHH02PvXjxgitXrmBnZ2d6LCIiggYNGrB//342b95M2bJl+fzzz/n8889Ny/Xjg8S1yDs/qlevDsDq1avZvHkzY8eOpXnz5oSGhjJhwgSSJUtGu3btTNt99dVXrFy5kvz58ydU00VE4o2ynkjcUtaTpEpZT8yZsp6IxJUE+YYyGo2Eh4eb/j5v3jyWLVtGvXr1aNKkCV5eXgwZMgRXV1dmzZqFo6Mj8+bNY/HixSRPnpy1a9diZWUVbR8i8krkhee2bdsICwvDz88Po9HI8ePHGTBgAD179qRx48akSJGCY8eOcfbs2Rj70DRAYm4aNWpEaGgo06ZNi/bjgdFoJHny5Pj4+BAWFga8eg/Y2tri6OiIjY0NNjY20falcCbx4fXRjU+fPsXf358RI0Zw//59WrduTffu3Zk8eTJz5syJtm7hwoWxsrIyncMiIomZsp5I/FHWk6RIWU/MnbKeiMSVjz4cKrLQZeQF4IULF7C2tmbUqFGmQpefffYZnTt3Jjw8nOHDh7NkyRIVuhR5h6gjwGbNmsWsWbPImzcvNWrUYNmyZXh4eDB+/Hhq1KgBQEBAAJkyZSJz5swJ2WyRd2rYsCHBwcEsW7YMe3t7UyF6AHd3d/LkycPUqVPJkiULX3zxBQaDgcDAQJ48eUKJEiUSuPXyKYitHlKrVq2wt7dn7dq1DB06lIEDB9KmTRvg1R0iL168oHv37tG20XWNiCR2ynoi8UNZT5IqZT0xd8p6IhKXPuqQEU9PT2bPnm36+8mTJ6lbty7jxo0jKCjI9HjkvLq7d++mf//+PH78mHTp0pEyZUoMBoMKXYrEIjKcbd++nYcPHzJnzhzc3NzInDkzLVu2xNnZmfPnz3Pr1i1Onz7N4MGDsbW1pXTp0gnccpE38/DwAIg1nP3xxx8ATJkyhaxZs9KlSxcGDx7MtGnTaNOmDf7+/rRt2zbB2i5J34ULFwBM1yaRIiIiAGjcuLGpZsvQoUO5f/8+bdq0oWXLlhw7dizaNiIiiZ2ynkj8UdaTpEhZT8yZsp6IxIeP2hmnQpci8cvPz4/u3buzbNkyLl++DICjoyN169alVatWeHl5UbNmTXr37s3Lly9Zvnw5lpaWmgZIzNKsWbM4fvw4jRs3jhHOOnXqxOTJk3n+/Dm2trYsXbqUGjVqcPXqVf766y+yZcuGl5eXprmSeDNixAh69+7N/v37geghzcLCIlpIq1u3Lnfv3mX48OH4+vrSrVs3fvvttxjBTkQkMVPWE4lfynqSlCjriTlT1hOR+GIwfoRPhtdv6Y1a6DJ9+vTMmzePCRMm0LVr12iFLgFOnz5N/vz5NTpSJBaR762o77EzZ87QpUsXXF1dGTFiBG5ubgCEhYXx/PlzLl26ROrUqcmZMycWFhaaBkjM1pEjR1i0aBEPHjzg//7v/6hWrRoAnTt35saNG8yePZuMGTNGm7YnMDAQKysrU5DT+S3x5fLly/Ts2ZOUKVPSsmVLypUrB0S/5gkPDzdN1bZixQqmT59O3bp1TVOWxDbliYhIYqOsJxI/lPUkKVPWE3OmrCci8eWjdMa9bv78+WzcuBE3Nzf69+9PunTpmDt3LhMnTqRbt26x3mquL1mR6KJelD569MgUttKmTcupU6do164dhQoVYsiQIWTIkOGd+xAxR8ePH2f+/Pk8ePCArl27smHDBi5fvszMmTOj1cCI7UJXF78S37y9venSpQspU6akVatWbwxpT58+JVWqVBw8eJCSJUuaQpuISFKkrCfy4ZT15FOgrCfmTFlPROJDvHfGvekLctmyZaxduxZXV1cGDhxoCmlTp07l//7v/2IUuhSR/4n6vpo5cyYHDx7Ex8cHOzs7WrRoQcOGDTlz5gytW7emSJEiDB48GBcXlwRutcj7i3qOR4a006dPY2lpyfbt23FyctIPDGIW3hTSIl2+fJnOnTtTpUoVunXrBkQfRSkikpgp64nEPWU9SeqU9SSxUNYTkbgWb99sKnQpEj8iIiJMF67Tpk1j8eLF1K9fnw4dOlCuXDmGDh3KtGnTKFSoELNnz+b06dN07dqVx48fJ3DLRd5f1O+O4sWL07p1awoVKkTKlCk5evQo8Gqudn1XSELLkSMHU6ZMwd/fn/nz57Nv3z7TskuXLvHzzz9jY2NDx44dTY8rnIlIYqesJxI/lPXkU6CsJ4mFsp6IxLV4uTNuxIgRHD58mN69e1O2bFkg+siXqCNcli5dipeXF5kyZaJv3764uLjEOje6yKfut99+4/vvv8fGxgaAu3fv0r17d9q2bUv58uVN6y1atIhRo0Yxffp0KlasyLFjx5g7dy5z5szRyDJJdGIbNXn//n3at29PpUqVYqwjklBeHzXp6upKnz59CA0NxcvLC2tra03DJiJJgrKeSNxT1pNPkbKeJBbKeiISV+Llau3777/HYDBEGzUQdeSLhYUF4eHhAHh4ePDjjz9y8uRJfvvtt2jr6gtX5JX69evz+++/RwtYL1684MqVK9jZ2Zkei4iIoEGDBpQuXZrNmzcTEhLC559/zrx587CwsDCNVhYxN28aF/L6qMlWrVqRLl065syZw6ZNm0zriCS0yFGTT548Ydq0abRq1YqQkBCFMxFJcpT1ROKWsp4kdcp6ktgp64lIXImXzrjcuXMzefJkHj9+/MaQZmlpSXh4OI8fP6ZBgwaMHj2aLl26mPahL1yRVxo1akRoaCjTpk2L9uVuNBpJnjw5Pj4+hIWFAa9+/LC1tcXR0REbGxvTyMpIGi0p5ijqdDyRf4/639imMbGysuLPP//8+I0VeYscOXIwefJkfH19SZ06NevXr1c4E5EkR1lPJO4o60lSp6wnSYWynojEhXiZpjKSCl2KfJiGDRsSHBzMsmXLsLe3JzQ0FGtra9Pydu3acf78ecaPH88XX3yBwWAgMDCQtm3bUqJECTp06JCArRd5t6gj4xcuXMjZs2dxdnbGw8ODbNmyRZvqKuq6ly5dwt3dXT86iFny9fUlbdq0WFpaKpyJSJKlrCfyYZT1JKlT1pOkSFlPRD5EvHbGwZtD2qVLl/D09CQsLMx0W6+I/I+Hhwfh4eH8+uuvMcLZH3/8Qfny5QkODqZly5Zcu3aNypUrkyZNGo4ePcqTJ09Yt26dLgok0Zg+fTpLliyhYMGC3LlzBysrKyZMmIC7u/sbQxpEr0sjYm70o7OIJHXKeiL/jbKefEqU9SQpUtYTkf8i3r/VIufV9ff3N01jcvXqVfr27RstnEVOvSAiMGvWLI4fP07jxo1jhLNOnToxefJknj9/jq2tLUuXLqVGjRpcvXqVv/76i2zZsuHl5YWVlZWpXoeIuYla0yIiIoInT54wY8YM5s+fT79+/UiZMiVdu3blypUr0WpgvD6tlcKZmDOFMxFJ6pT1RP49ZT1J6pT15FOgrCci/0W83xkXydvbm65du2Jra8uDBw9IliwZ69at0/y6IrE4cuQIixYt4sGDB/zf//0f1apVA6Bz587cuHGD2bNnkzFjxmgjxQIDA7GysjIFOb2vxFxFPW937drFrVu3WLVqFUOGDKFkyZIA7Nu3j19++YVHjx4xefJkcuXKFWOkpIiIiJgHZT2R96esJ0mZsp6IiMibfbTOOHgV0po1a0a6dOlYtWoVVlZWuogUeYPjx48zf/58Hjx4QNeuXdmwYQOXL19m5syZZM6c2bRebBetupCVxGDcuHEsWrSIbNmycfXqVX7++WcaNGiAnZ0dAPv372fBggVcuHCBNWvWRDvvRURExLwo64m8P2U9SeqU9URERGL6qMkoR44crFmzRoUuRd4iMlwVL14cgPnz59O7d28sLS3Zvn07Tk5O0UabxRbEFM7E3J05c4YTJ06wbNky0qZNy8qVKxk3bhwODg7UrFkTOzs7ypYtS0hICEeOHMHV1TWhmywiIiJvoawn8m7KevIpUNYTERGJ3UdPRy4uLsCrQpcKZyIxGQyGaCHNYDAwd+5c7t69y9GjR6lQoQIWFhYaESmJ1vLly7lw4QIuLi4ULlwYgG7duhESEsKQIUMAqFWrFra2tlSsWJGKFSsCKpAsIiJi7pT1RN5OWU+SOmU9ERGRN0uwaqj6khV5s8iQBlCsWDFat25NxowZmT59Ort27Yqxjkhi8uzZM9atW8fJkye5evWq6fE+ffrQvHlzhg8fzvLlywkJCYm2nb43REREEgd9Z4u8mbKeJGXKeiIiIm+WYJ1xIvLKm0JW1ABWvHhxWrVqRbp06ZgzZw6bNm0yrSNiziIiImI81rZtW4YMGUJwcDBLlizh+vXrpmW9evWidu3a7N6921SgXkREREQkMVLWk6RMWU9EROTfMRg13EokwUStBxD171EfjzpFyYkTJxg3bhzZsmVj1KhRCdJmkfcV9Tw+cOAAjx49wtfXl5o1a+Lq6sqaNWuYOHEilStXpmnTpmTLls20beR5ryl6RERERCQxUtaTpExZT0RE5N9TZ5xIAol64blw4ULOnj2Ls7MzHh4eZMuW7Y0h7dKlS7i7u0cLdiLmbNy4cWzZsoVkyZLx8OFDjEYjnTp1onHjxqxatYqpU6dSpUoVGjRoQM6cOU3bKZyJiIiISGKkrCefCmU9ERGR96eq2iIJJPLCc/r06SxZsoSCBQty4cIFjh49yoQJE3B3dzeFtKijxvLkyQPEHGkpYo5Wr17Nxo0bmTVrFpkyZSJ58uT06tWLadOm4ezszI8//khwcDAjRowgY8aM0QKawpmIiIiIJEbKevIpUNYTERH5d3RnnMhHFjVYRUREMHLkSKpUqULx4sU5ePAgc+fO5eHDh0yePDlaSBMxdytWrKBo0aK4u7ubHhs9ejQhISEMHDiQ0NBQU22Adu3acf36dbZv346FhQU7duygYsWKKtwtIiIiIomWsp4kVcp6IiIiH05XfSIfUdSwtWvXLn799Vf2799PaGgoAGXKlKFly5akSZOGbt26cfXqVSwsLN5Y+FvEXBw6dIjBgwezbNkyU5HuiIgIzp8/z+3btwGwtrYmODgYgPbt23Pv3j3Onj0LQOXKlbG0tCQ8PDxhDkBERERE5AMo60lSpawnIiISN9QZJ/IRRYazcePG0a1bNzZs2MA///zD5cuXCQoKAqBcuXK0atWKdOnS4eHhwe3btzWFg5i90qVLM3ToUH7//XcWLVpk+nHhq6++wsfHhz/++AMAW1tbAF68eIGbmxsuLi7R9qPRkiIiIiKSGCnrSVKlrCciIhI3VDNO5CM7c+YMJ06cYNmyZaRNm5aVK1cybtw4HBwcqFmzJnZ2dpQtW5aQkBCOHDmCq6trQjdZ5K1CQkKwsbHhxx9/5Pnz5yxevBiDwUD79u2pWrUqmzZtYvHixQQFBVG1alX8/PxYvHgxGTJkIF26dAndfBERERGROKGsJ0mNsp6IiEjcUc04kY9o+fLlXLhwgefPnzN58mTT42PGjGHx4sUMGjSIWrVqmUaURQoPD9coMjFLkcXmAWbMmIG/vz/r168nICCAevXq0bt3b+7fv0+/fv24c+cO4eHhpE2bFmtra1auXIm1tbVqZYiIiIhIoqesJ0mNsp6IiEjc0p1xIh/Rs2fPWLduHalSpeLq1avkypULgD59+mBhYcHw4cN5+fIljRo1wsbGxrSdwpmYq8hwtnDhQhYuXMikSZOoVasWp0+fZsGCBUyYMIHu3bsze/ZsLl26xOXLl8mSJQtff/01lpaWhIWFYWWlryIRERERSdyU9SSpUdYTERGJW7ozTiSevGkE2Nq1axk7diyVK1emefPmZM+e3bRs4MCBXL9+nSVLlqh2gCQKkaMlO3TogJubG7169TItW79+PePGjaN8+fK0adOGLFmyRNtWo4BFREREJDFS1pNPgbKeiIhI3NIQFZF4EDWcHThwgEePHuHr60vNmjWpV68eRqORiRMnYmlpSdOmTcmWLRsAQ4cONV3wRp0SQsSchYSE8OjRIzJkyABAaGgo1tbW1K5dm8uXL7N8+XJCQkLo0KEDWbNmNW2ncCYiIiIiiY2ynnxKlPVERETijjrjROJBZDgbN24cW7ZsIVmyZDx8+JCFCxfSqVMnGjduTEREBFOnTsXS0pIGDRqQM2dOAIUzMWuvjwI2GAzY2NhQuHBh1q1bR4sWLciYMaNpvdSpU5MhQwYcHBzInDlzArZcREREROTDKetJUqWsJyIiEr/UGScST1avXs3GjRuZNWsWmTJlInny5PTq1Ytp06bh7OzMjz/+SHBwMCNGjCBjxoymgAYonIlZihrO1q5dy61bt7CwsKBr16506NCBkydP0qRJE2bOnEn69Omxs7Pj6NGj1K9fn2bNmmEwGFTAW0REREQSPWU9SWqU9UREROKfasaJxIEVK1ZQtGhR3N3dTY+NHj2akJAQBg4caJrKAaBdu3Zcv36d7du3Y2FhwY4dO6hYsaKmcRCzFnUE7+jRo1m5ciVubm5cv36dAgUKMGPGDO7evcvo0aM5ffq0KaCFh4ezYcMGrKysFM5EREREJNFR1pOkTllPRETk41BnnMgHOnToEC1btjSNCMuePTsRERE0a9YMOzs75s2bB0BwcDC2tracPn0aDw8Pli5dSuHChU37UYFjSQxu375Nnz59GDhwIK6urty8eZOuXbuSMWNGpk+fTooUKdi4cSNBQUHY2dlRvXp1LC0tdX6LiIiISKKjrCefEmU9ERGR+KVhKyIfqHTp0gwdOpTff/+dRYsWcfXqVSwsLPjqq6/w8fHhjz/+AMDW1haAFy9e4ObmhouLS7T96OJVzN2qVavo0aMHjo6Opul4ChUqxMSJE7lz5w7t2rUjICCAmjVr8uOPP1KzZk2FMxERERFJtJT15FOhrCciIhL/1Bkn8gFCQkIA+PHHH2nRogV79+5l2bJl+Pn5UbVqVaysrFi8eDHbtm0DwM/Pj8WLF5MhQwbSpUuXkE0X+VeCg4MJDw/n8ePH3Lp1CycnJ+DVlCafffYZkydP5tGjR9StW5eAgIBo2yqciYiIiEhio6wnnwplPRERkY9D01SK/EdR51WfMWMG/v7+rF+/noCAAOrVq0fv3r25f/8+/fr1486dO4SHh5M2bVqsra1ZuXIl1tbWmlddzFZs5+bLly/ZuXMnQ4YMoXz58kycOBH433vh+PHjLF68mEmTJimUiYiIiEiipawnSZmynoiISMJQZ5zIB1q4cCEzZsxg0qRJpEiRgtOnT7NgwQJKly5N9+7diYiI4NKlS1y+fJksWbLw9ddfY2lpSVhYGFZWVgndfJEYooazzZs3c/HiRdzd3fnqq69IlSoVXl5eDBkyhEqVKjF+/Hgg+g8WoLoYIiIiIpL4KetJUqOsJyIiknDUGSfyH0VekHbo0AE3Nzd69eplWrZ+/XrGjRtH+fLladOmDVmyZIm2rS5exVxFDVpjxozBy8sLFxcXbty4wffff0+rVq1wdXXFy8uLoUOH8u233zJ27NgEbrWIiIiISNxR1pOkSFlPREQkYWmolsgHCAkJ4dGjR2TIkAGA0NBQrK2tqV27NpcvX2b58uWEhITQoUMHsmbNatpO4UzMVWQ4W7BgAZs2bWLmzJkUK1aMgQMHsn79egwGA61ataJOnToYDAY8PT3JkiULHTt2TOCWi4iIiIjEHWU9SWqU9URERBKWOuNE3tPr86obDAZsbGwoXLgw69ato0WLFmTMmNG0XurUqcmQIQMODg5kzpw5AVsu8v5CQ0MBOHLkCG3atKFYsWKcPn2aEydOUL58edavX09ERARt2rShTp06pEqVitKlSydwq0VERERE/jtlPfkUKOuJiIgkLFUTFnkPUcPZ2rVrmThxIpMnTwYwjYRs0qQJly5d4unTpwQGBnL06FHq16/PoEGDsLCwICIiIgGPQCR227ZtY926dezcuRMAa2trnj59ire3N8mTJ8fPz49Vq1ZRvXp1JkyYQPXq1VmzZg2dOnXi9OnTlCtXDisrK8LCwhL4SERERERE/j1lPUmqlPVERETMi+6ME3kHo9FoCmejR49m5cqVuLm5cf36dY4dO8aMGTMYMmQIo0ePpn79+qRPnx47OzvCw8Px8PDAYDDEGGkpYg7atWuHt7c3fn5+WFhYsGfPHkaPHk2aNGlo0aIF2bNn5/jx4zx+/Jg6deoA4OjoSK5cuShdujQFChQw7UsF6kVEREQksVHWk6RKWU9ERMT86BtV5B0i51W/ffs2Z86cYfny5bi6unLz5k26du1Kp06dmD59OosXL2bjxo0EBQVhZ2dH9erVsbS0VAFvMUsNGzYkJCSEadOmER4ezp49e1i0aBHbt2+nSpUqNGrUCIPBwNy5c3F1daV48eIA3Lhxg3r16pmW6/wWERERkcRKWU+SImU9ERER86TOOJH3sGrVKtasWUOKFCnIlCkTTk5OFCpUiIkTJ9K9e3fatWvHvHnzqFmzZrTtdPEq5qhhw4YEBwezdOlSHBwcALC1tWXx4sUEBwcD//thwsHBgT179pA3b142bNjA06dPqV+/PgaDAaPRqPNbRERERBI1ZT1JSpT1REREzJfmUhB5h+DgYMLDw3n8+DG3bt3CyckJeDWlyWeffcbkyZN59OgRdevWJSAgINq2ungVc9O8eXNCQ0NZvXo1Dg4OhISEAJAxY0bc3d1JkyZNtPWbNWuGq6srS5YswcnJibVr12JlZUV4eLgpxImIiIiIJEbKepKUKOuJiIiYN90ZJ/Ka1+f8t7W1pVatWtjb2zNkyBC6d+/OxIkTTaPFChUqxMiRI1m8eDH29vYJ2HKRt5s7dy5HjhyhX79+ph8PbGxsABg+fDgnTpzg1q1b3Lt3D1dXV7Jnz07+/PmZP38+4eHhODo6YjAYCAsLU90AEREREUl0lPUkqVLWExERMX8Go9FoTOhGiJiLqOFs8+bNXLx4EXd3d7766itSpUqFl5cXQ4YMoVKlSowfPx54NWoy6qgxTVci5ur27duMGDECf39/atasSePGjQHo3Lkzhw4dwtnZmdSpU3PmzBng1Y8Tjo6OdOjQwbSuCtSLiIiISGKkrCdJmbKeiIiI+VNnnMj/FzVojRkzBi8vL1xcXLhx4wbff/89rVq1wtXVFS8vL4YOHcq3337L2LFjE7jVIv+Oj48Pw4cP5/HjxzRq1Ig9e/Zw8+ZNxo4di4uLC8mTJ+fKlSv4+flx5swZ7t27x9ChQzU6UkREREQSLWU9+RQo64mIiJg3dcaJvGbBggX88ssvTJkyhWLFijFw4EA2b95MnTp1aNWqFS4uLqxfvx5PT086duxIx44dE7rJIv9KZEg7e/YsBoOBNWvW4OLi8tZtNF2JiIiIiCR2ynqS1CnriYiImC/dfy7y/4WGhhIaGsqRI0do06YNxYoV4/Tp05w4cYLy5cuzfv165s6di6+vL3Xq1GHOnDm0a9cuoZst8q9lypSJgQMHUqhQIdKkScOBAwdMy8LDw2PdRuFMRERERBIrZT35VCjriYiImC91xskna9u2baxbt46dO3cCYG1tzdOnT/H29iZ58uT4+fmxatUqqlevzoQJE6hevTpr1qyhU6dOnD59mnLlymFlZUVYWFgCH4nIv+fq6kq/fv1wcXFh5cqVrFy5EgBLS0t0w7SIiIiIJGbKevIpU9YTERExTxr+Ip+kdu3a4e3tjZ+fHxYWFuzZs4fRo0eTJk0aWrRoQfbs2Tl+/DiPHz+mTp06ADg6OpIrVy5Kly5NgQIFTPvSKDJJrDJlykT//v0ZPnw4Xl5eBAYG0rx582hF6kVEREREEhNlPRFlPREREXOkO+Pkk9OwYUMePHjAtGnTWL58OS1btmT37t1s374dgEaNGlGoUCG2bduGq6srxYsXB+DGjRvUq1ePrl27Ymlp+cYpHkQSk8iQZjAYuHr1qkZKioiIiEiipawn8j/KeiIiIuZFw7zkk9KwYUOCg4NZunQpDg4OANja2rJ48WKCg4MBTCPFHBwc2LNnD3nz5mXDhg08ffqU+vXrYzAYMBqNWFpaJthxiMSlTJkyMXXqVNKkSWM6vzViUkREREQSE2U9kZiU9URERMyH7oyTT0bz5s0JDQ1l9erVODg4EBISAkDGjBlxd3cnTZo00dZv1qwZrq6uLFmyBCcnJ9auXYuVlRXh4eG6eJUkJ126dFhYWBAREaHzW0REREQSFWU9kTdT1hMRETEPujNOPglz587lyJEj9OvXzzTK0cbGBoDhw4dz4sQJbt26xb1793B1dSV79uzkz5+f+fPnEx4ejqOjIwaDgbCwMNUNkCTNwkJjNEREREQk8VDWE3k/ynoiIiIJy2DUpNHyCbh9+zYjRozA39+fmjVr0rhxYwA6d+7MoUOHcHZ2JnXq1Jw5cwZ4NZ2Jo6MjHTp0MK0bERGhi1cREREREREzoqwnIiIiIomBOuPkk+Hj48Pw4cN5/PgxjRo1Ys+ePdy8eZOxY8fi4uJC8uTJuXLlCn5+fpw5c4Z79+4xdOhQjY4UERERERExY8p6IiIiImLu1Bknn5TIkHb27FkMBgNr1qzBxcXlrdtouhIRERERERHzpqwnIiIiIuZM8zDIJyVTpkwMHDiQQoUKkSZNGg4cOGBaFh4eHus2CmciIiIiIiLmTVlPRERERMyZ7oyTT1LkqMmHDx/yww8/UL9+fQCMRiMGgyGBWyciIiIiIiL/hbKeiIiIiJgjdcbJJysypPn7+1O1alWaN2+e0E0SERERERGRD6SsJyIiIiLmRtNUyicrU6ZM9O/fH4PBwNWrV1G/tIiIiIiISOKnrCciIiIi5kZ3xskn7/79+6RJkwYLCwtNXSIiIiIiIpJEKOuJiIiIiLlQZ5zI/xcREYGFhW4WFRERERERSUqU9UREREQkoakzTkRERERERERERERERCSeaGiYiIiIiIiIiIiIiIiISDxRZ5yIiIiIiIiIiIiIiIhIPFFnnIiIiIiIiIiIiIiIiEg8UWeciIiIiIiIiIiIiIiISDxRZ5yIiIiIiIiIiIiIiIhIPFFnnIiIiIiIiIiIiIiIiEg8UWeciIiYTJs2jdy5c5M7d26WLVv21nUrVKhA7ty5adKkSZy24a+//iJ37txMmzbtP23/vm3KnTs3+fLl49SpU29cp0mTJuTOnfs/tUNERERERMRcKOtFp6wnIiIfmzrjREQkVtu3b3/jslOnTnHnzp2P2Jr4ER4ezs8//0xwcHBCN0VEREREROSjUNYTERH5+NQZJyIiMWTNmpXjx4/z8OHDWJdv3bqV1KlTf+RWxY8bN24wadKkhG6GiIiIiIhIvFPWExERSRjqjBMRkRiqVq1KREQEO3fujLHMaDSyfft2qlSpkgAti1v58+cnU6ZMLFq0iBMnTiR0c0REREREROKVsp6IiEjCUGeciIjE8OWXX5IqVapYpy85fvw4fn5+VK9ePdZtnz59yujRo/nmm28oUKAAJUuWpHv37nh7e8dY9+LFi7Rr147PP/+c4sWL07t3bx49ehTrfq9fv0737t0pWbIkBQoU4Ntvv2Xy5MkEBQX95+N0dHRk5MiRGI1G+vbtS2Bg4Du3CQ0N5ZdffqFevXoUKVKEAgUK8PXXX9O/f/9obY+sh7B582amT59OhQoVKFiwIN999x07d+4kLCyMWbNmUaFCBT777DPq1KnD/v37YzzfmTNnaNeuHV988QUFCxakRo0a/Prrr4SHh//n4xYRERERkU+Tst6bKeuJiEh8skroBoiIiPmxsLCgUqVKrFmzhocPH5ImTRrTsi1btpAhQwaKFi0aY7uHDx/SsGFDbt++Te3atSlUqBA+Pj4sX76cPXv2MH/+fIoXLw7A+fPn8fDwwMbGhqZNm5IsWTI2btzI7t27Y+z3zJkzNG/eHCcnJxo3bkyqVKk4deoUs2fP5vDhwyxevBhbW9v/dKwlSpSgcePGLF26lAkTJtC/f/+3rt+1a1d+//136tSpw48//khwcDD79+9n9erV3L17l19//TXa+uPHj8fe3p6mTZsSGhrKvHnz6NatG6VKleLu3bs0bdqUsLAw5s2bR8eOHdm6dSuZMmUC4Pfff6dLly5kypSJVq1a4eDgwKFDhxgzZgwnT55k2rRpGAyG/3TcIiIiIiLy6VHWezNlPRERiU/qjBMRkVhVq1aNlStXsnPnTho1agS8KoK9c+dOateuHWswmDhxIv/88w8jR46kXr16psfr1KlDnTp16Nu3L9u2bcPS0pLRo0cTEhLC6tWryZkzJwCNGjWiefPm0aYRiRzJmDx5ctavX4+zs7Np3c8//5z+/fuzePFiWrdu/Z+PtUePHuzfv5+lS5dSuXJlPv/881jXu3TpErt376ZJkybRglzTpk35/vvvOXToEE+ePDG1ESAsLIzVq1fj5OQEgI2NDSNHjuTSpUts27bN9LijoyODBw/m8OHD/PDDDwQGBtKvXz/c3d1ZsWIFNjY2AHh4eDB58mRmzZrFtm3bqFat2n8+bhERERER+fQo68WkrCciIvFN01SKiEisvvjiC9KkSRNt+pIjR47w6NGjWKctiaw7kDVrVurWrRttWa5cuahVqxa3bt3i/Pnz+Pv7c/z4cb766itTOINX4aVFixbRtr18+TJXr16lXLlyRERE8PjxY9Of8uXLY2try65duz7oWB0cHBg1ahQAnp6evHz5Mtb18uTJw4kTJ+jevXu0xx89ekTy5MkBYmxbtmxZUwgDTMf79ddfR3s8a9asAPj5+QHw559/4u/vT+XKlQkICIh23JGh7EOPW0REREREPj3KejEp64mISHzTnXEiIhIrCwsLKleuzIoVK3j06BGpU6dm69atuLm5kT9//hjr+/v78/z5cz7//PNYR1LmypULAB8fHwwGAxEREaZQElXUwAZw48YNAFasWMGKFStibeudO3f+9fG9rnjx4jRp0oTFixczfvx4Bg4cGOt6NjY2bN26lUOHDnH79m18fHx48OCB6ZgjIiKirZ82bdpof7eysor1cUtLS+DV6FD433FPnDiRiRMnxtqWuDhuERERERH5tCjrKeuJiMjHp844ERF5o6pVq7Js2TJ27tzJ999/z+7du2ncuHGs60YGizfNax8ZXCKn4Ii6TWzrvf73xo0bU7FixVj3HRl6PlT37t3Zv38/v/32G99++22M5QEBATRr1ozz589TrFgxChQoQK1atShYsCCLFi1i48aN7922d83/H3ncnTt3pkiRIrGu4+jo+K5DEhERERERiUFZLzplPRERiW/qjBMRkTcqVqwY6dKlY9u2bWTIkIEnT57EOm0JQKpUqXBycuLatWsYjcYYAeTq1asAZMiQgYwZM2JhYYG3t3eM/dy6dSva3yMLXAOUKlUq2rKIiAh27NhB5syZ/9Pxvc7e3p6RI0fi4eFB3759o9UDAFi8eDHnzp1jyJAhNGjQINqyhw8fxkkbIkUet52dXYzjDggI4ODBgzFGXIqIiIiIiLwPZT3naMuV9UREJL6pZpyIiLxR5PQlx48fZ/ny5eTJk4ccOXK8cd1KlSpx69YtvLy8oi3z9vZm06ZNZM6cmXz58uHs7EypUqU4dOgQp06dMq0XHh7OggULom1boEABMmbMyLp16/jnn3+iLVu5ciVdu3Zl7dq1cXPAvAqlzZo1486dO5w/fz7aMn9/fwBy584d7fG///6bY8eOmY4hLpQpUwZHR0cWLlxoet5Is2fPpkuXLuzbty9OnktERERERD4tynrKeiIi8nHpzjgREXmratWqsWTJEvbu3UuPHj3eum6PHj04evQo/fr149ixYxQuXBgfHx9WrFiBpaUlI0eONI2i7N+/Pw0aNKBFixZ4eHiYRmXevHkz2j4tLS0ZPnw4bdu2pW7dujRo0IAsWbJw9uxZ1q5dS5YsWfjpp5/i9Ji7du3K3r17TXP5R6pQoQJLliyhZ8+eNGrUiGTJknHu3DnWrVuHpaUloaGhPHv2LE7akDx5cgYOHIinpyffffcd9evXJ126dBw5coStW7dSqFAhGjVqFCfPJSIiIiIinx5lvf9R1hMRkfimzjgREXmrIkWKkCFDBu7du0e1atXeum7atGlZs2YNM2fOZM+ePWzevBlnZ2cqVKhAu3btoo20zJYtG6tWrWLSpEmsWrWKkJAQSpUqRZcuXWjatGm0/ZYqVYpVq1Yxa9Ys1q5dy/Pnz3FxcaFRo0a0bds2zqfwsLOzY9SoUTRq1ChaXYOSJUsyceJE5s2bx/Tp07GxscHV1ZWuXbuSM2dO2rRpw4EDByhYsGCctKN27dpkyJCB+fPns3jxYoKDg3F1daV9+/a0bNkSBweHOHkeERERERH59CjrKeuJiMjHYzDGVlFVRERERERERERERERERD6YasaJiIiIiIiIiIiIiIiIxBN1xomIiIiIiIiIiIiIiIjEE3XGiYiIiIiIiIiIiIiIiMQTdcaJiIiIiIiIiIiIiIiIxBN1xomIiIiIiIiIiIiIiIjEE3XGiYiIiIiIiIiIiIiIiMQTdcaJiIiIiIiIiIiIiIiIxBN1xomIiIiIiIiIiIiIiIjEE3XGiYiIiIiIiIiIiIiIiMQTdcaJiIiIiIiIiIiIiIiIxBN1xomIiIiIiIiIiIiIiIjEE3XGiYiIiIiIiIiIiIiIiMQTdcaJiIiIiIiIiIiIiIiIxBN1xomIiIiIiIiIiIiIiIjEE3XGiYiIiIiIiIiIiIiIiMQTdcaJiIiIiIiIiIiIiIiIxBN1xomIiIiIiIiIiIiIiIjEE3XGiYiIiIiIiIiIiIiIiMQTdcaJiIiIiIiIiIiIiIiIxBN1xomIiIiIiIiIiIiIiIjEE3XGiYiIiIiIiIiIiIiIiMQTq4RugIhIUufj48M333xj+nuTJk3o37//O7f75ZdfGDt2LADp06dn//79b11/4MCBrFy5EoBJkyZRrVq1t67/888/s27dune2I6oZM2ZQsWLFf7UNQEhICJs3b2bnzp1cuHCBx48fY2VlRYYMGfj888+pX78++fPn/9f7/ZT99ddfNG3aFIDz589jZaWvdBERERGRN8mdO/dbl1tZWeHo6EimTJn46quvaNmyJcmTJ4+2zsOHDxk/fjyHDh3iyZMnpE2blrJly9K1a1ecnZ3fuy0hISF4eXmxe/duLl++jL+/Pw4ODqRLl44SJUpQu3ZtChYs+F8OM0l5/Pgxa9asYf/+/Vy9epWAgADs7e1xc3OjTJkyNGzYkPTp0yd0MxOVadOmMX36dIoWLcry5csTujkiIp8U/XInIvKR7dixg379+mEwGN663tatW997n0FBQWzZssX09+XLl7+zMy6Sk5MT7u7u77XuvwmYkU6dOkX37t25c+cOAMmSJSNHjhwEBgZy+/Ztrl+/zqpVq2jcuDGenp7qVBIRERERkXjj5uZGqlSpYjweEhLC7du3OX/+POfPn8fLy4tVq1aRIUMG0zrt2rXjwoUL9OrVizx58rBv3z4WLFiAn58fs2bNeq/n/+eff2jVqhW3bt3CYDCQOXNm8uXLR3BwMDdv3uTq1assW7aMhg0bMnDgwHfmxqRqzZo1jBgxgpcvXwKQOnVqcufOzcOHDzl37hxnz55l0aJF9OvXj++//z6BWysiIvJu+sVTROQjsrKy4v79+5w4cYLixYu/cb3bt29z7ty5997v9u3bCQgIoGTJkhw/fpyjR4/i7e1Njhw53rltvnz5WLJkyXs/17+xdetWevXqRVhYGKVKlaJTp04ULVrUtPzZs2csWLCAuXPnsnTpUp49e8a4cePipS1JTaFChUwdturAFBERERF5P23btqVu3bqxLouIiGDTpk3069eP+/fv4+npycKFCwHw9/fns88+o1KlSrRo0QKAkiVLsm7dOv7666/3eu6QkBBat27NrVu3+Oabbxg0aFC0O7uCg4NZvXo1I0eO5LfffiNlypR07tz5ww44ERo2bBhLly7FYDDQoEEDWrduTaZMmUzLb926xcSJE9m+fTv9+vXDaDTyww8/JGCLE4/GjRtTrVo17O3tE7opIiKfHNWMExH5iL788kvgVefZ20R2suTLl++99rt27VoAypYtS4kSJQBYsWLFf21mnLh58yb9+vUjLCyMunXr8ssvv0TriANInjw5Xbp0YciQIQBs3LiRXbt2JURzEx17e3ty5MjxXh2uIiIiIiLybhYWFtSqVYvWrVsDcPjwYW7cuAFAypQp6d+/P23btjWtv2/fPp48efLeM41s27aNmzdv4urqyuTJk2NMsWhra4uHhwc//fQTAAsWLCAgICAuDi3R2LJli6kjbtiwYQwZMiRaRxxA1qxZmTJlCrVq1QJgxIgR+Pr6JkRzE51UqVKRI0cOXF1dE7opIiKfHHXGiYh8RFWqVAFg586dGI3GN663detWLCwsqFq16jv3efv2bY4dOwZAuXLlTM+xYcMGgoKC4qDV/83w4cN5+fIlrq6uDBkyBAuLN3/lfP/99xQuXBh4VStPREREREQkoZQvX970/9euXYt1nWXLltGhQwesra3p2bPne+337NmzAOTJkwcbG5s3rvfjjz8C8PLlS65cufK+zU70AgMDGTp0KABVq1Z9591uP//8Mw4ODgQGBqr+mYiImD3NayUi8hEVL16ctGnT4ufnx8mTJylWrFiMda5fv86lS5f48ssvSZMmzTv36eXlhdFoJHv27OTIkYO0adMyZMgQnj59ypYtW6hXr158HMpb3b17l4MHDwLQrFmztwbNSH379sXf3z/G3XPwqibeihUr2Lp1K9euXSM0NJT06dNTqlQp/u///g83N7do6//11180bdqUokWLsmjRIn799Vc2bNiAj48PyZMnp3Tp0vTo0YP06dPj4+PD9OnTOXjwIE+ePMHFxYXq1avToUOHaO328vLC09OTb775hjFjxjB58mR27dpl2qZChQq0bNmStGnTxmi/0Whkz549bNiwgbNnz/Lo0SMA0qRJQ7FixWjatGmMAu0///wz69atY/DgwVhYWDBr1iwePXpEhgwZGDZsGABNmzYF4Pz589Gmqjx9+jQLFy7kwoUL3Lt3D1tbW7Jly0bFihVp1KgRTk5OcfYaFy5cmGXLlrFkyRLWr1/PrVu3sLa2Jn/+/DRp0oSKFSu+5V9dRERERMT8RB1I+PogysDAQDw9Pdm2bRvOzs5MmTLlrSUIorK2tgZeXa/7+/uTMmXKWNdLly4d69evx8nJKcbdc/Bquss1a9awadMmrl+/zosXL3B1daVs2bK0bds21kxy9uxZFi9ezLFjx3j48CEODg7kzp2bWrVqUadOHSwtLaOt36RJE44ePcrcuXM5d+4cy5Yt48WLF2TOnJkpU6aYZuh4+PAhv/76K3v37uXOnTtYWFiQPXt2qlevTuPGjbG1tX2v1wZe1Vd/8uQJAG3atHnn+qlSpWLcuHE4OztTqFChGMv9/PxYuHAh+/btM7UtS5YsVKpUiaZNm5I8efJo60+bNo3p06fTrl07PDw8mD59On/88Qf+/v6kT58+Wk7866+/mDt3LmfOnCE4OJgcOXLQrFkzateuHW2fkbnO09OTr776ikmTJnHs2DFCQkLImjUrderUoUGDBrG+TkFBQaxdu5bdu3dz+fJlnj17ho2NDa6urpQpU4YWLVrEOD8qVKjAnTt32LBhA2vWrGHDhg2EhYWRLVs2fv31V5YsWcL06dMpWrRojA7MLVu24OXlxfXr13nw4AHJkiUjX7581KpVixo1asQ6wPa/vsatW7fm//7v/5g5cyZ79uzh/v37JE+enBIlStCuXTty58791n97EZHESJ1xIiIfkYWFBZUrV2bp0qVs37491s64yCkqq1ev/s79RUREsH79egBq1KgBvJr6sVy5cuzevZsVK1YkSGfc4cOHTaG1dOnS77XNZ599Fuvjvr6+tGjRguvXrwOvCq47Ojri7e3NypUrWb9+PaNHj6ZatWoxtg0ODqZp06b8/fffZMqUiSxZsnDjxg02bNjAyZMnGTVqFO3atSM4OBg3NzesrKy4ffs2s2fP5vbt20ycODHGPgMCAmjUqBFXrlzB1dWVHDlycPXqVRYsWMCWLVuYP39+tOBgNBrp2bMnmzdvBiB9+vTkypWLJ0+ecPfuXTZu3MjWrVuZOXMm5cqVi/F8Gzdu5OTJk7i4uODm5oaPjw958+bl4sWLsb5eO3fupFu3boSFhZEyZUpy5szJixcvOHPmDKdPn2bjxo2sWLEiWofch7zGoaGhtG7dmsOHD5MyZUpy5MjBjRs3OHLkCEeOHGHw4ME0bNgw1raKiIiIiJijyExmYWERrZPn8ePHtGjRgkuXLlG4cGGmTJlChgwZ3nu/X331Fb/++iuPHj3ihx9+oEWLFnz77bexdp7lzZs31n3cv3+f9u3bm2qMZ82aFRcXF65fv86SJUvYvn07K1euJGPGjKZt5s2bx8SJE4mIiMDJyYncuXPj7+/P0aNHOXr0KBs2bGDmzJkkS5YsxvPNnj2bkydPkiVLFpIlS0ZAQIBpoN6JEyf46aefePLkCdbW1ri5uWE0Gjl//jznzp1jw4YNzJ8/P9bji83hw4eBV51sbzr+171p8N/hw4fp1KkTz58/x9rampw5cxIWFsaVK1e4dOkSa9asYc6cObF2+ty6dYtatWrh7+9Pzpw5sbS0jJYTP//8c4YMGYK9vb0po124cIE+ffoQFBREgwYNYuzz8uXLTJ06lZcvX5IrVy7CwsK4ePEiFy9eZMeOHcyZMyfa6//48WOaNWvGlStXMBgMZMmShQwZMuDn58fVq1e5evUqGzduxMvLCxcXlxjPN2TIEE6ePEnOnDkJDAzExsYGZ2fnN76Oo0aNMtVHzJgxI7lz5+b+/fscPHjQ9Gfs2LFx9hrfvXuX2rVrc//+fVOuvnLlClu3buWPP/5g2bJl5M+f/43tFRFJlIwiIhKvbt++bXR3dze6u7sbb968aTx27JjR3d3dWLZsWWNERESM9atVq2bMnz+/0d/f37h27Vqju7u78auvvop13wcOHDDt+59//jE9vn37dtPj58+fj3XbPn36GN3d3Y0eHh5xc6BRjB071uju7m7Mnz9/rMf4vsLCwoy1atUyuru7GytXrmy8ePGiadnz58+N/fr1Mz3PqVOnTMuOHDliOv4iRYoY9+7da1r2559/GnPnzm10d3c35smTx9i8eXOjn5+f0Wg0GiMiIoxTp041bXv79m3TdpH/Fu7u7sYCBQoYN23aZFrm6+trrF+/vtHd3d1YvXp1Y2hoaIztChUqFK0dRqPReO3aNWP16tWN7u7uxrp160ZbFvnv4+7ubhw6dKgxLCzMaDQajY8ePYpxjJHPFx4ebixdurTR3d3dOG/ePNM2RqPReO7cOeOXX35pdHd3N86ZMydOX+PPPvvMuHHjRtOyZ8+eGZs1a2Z0d3c3fvHFF9FeDxERERGRhBB57bp27do3rhMcHGxctGiRMW/evEZ3d3djv379oi2rU6eO0d3d3fjdd98Z//zzT+OxY8dMf6Jee79Njx49TG1xd3c35s6d21i9enXjoEGDjJs3bzZd779Jy5Ytje7u7saKFSsaz507Z3rcz8/PlEnq169vejxqNpw8ebIxODjYtOzw4cPGUqVKGd3d3Y3t2rWL9jweHh6m7ebOnWt6PLJ9vr6+xi+++MLo7u5u7N+/v/Hp06emdW7dumX84YcfjO7u7sZGjRq91+tiNBqN33//vdHd3d3YrFmz994mNj4+PsbPPvvMdFwPHjwwLfvnn39Mr9PXX39tfPbsmWlZ1CxYtWpV440bN0zLpkyZYlqWJ08e46hRo0yv5cuXL03/LuXLl4/Wlqi5rnz58sYLFy6Ylp08edL0+g8YMCDW7SpVqhStHUaj0bh//35j4cKFje7u7sbRo0dHW1a+fHnT823ZssX0eOS/W+QxNmjQwLTs2rVrRnd3d2PBggWNR44ciba/devWGfPkyWN0d3c3/v3333H6GleuXNl45swZ0zJvb29j2bJlje7u7sb27dsbRUSSGtWMExH5yIoVK0b69Onx9fXl77//jrbs8uXLXLt2jVKlSr111FqktWvXAlCkSBEyZ85serx8+fKm6SBWrFjx1n0cPXqU3Llzv/PPzz///N7H+PTpUwCcnZ0xGAzvvd3rtm/fzsWLF7G1tWXevHnkyZPHtMzJyYnhw4fz1VdfERoayqRJk2LdR7t27aLdcVayZEnTXXj29vZMnTqVdOnSAWAwGGjbtq1p+pg33X3Wp08f052I8Oput8iRpFevXmXHjh2mZYcOHcLKyopGjRrFuPMtR44ctGrVCuCNtSBsbW3p0aOHadqYVKlSxboevBo9+eDBA+BVnYmoU83kz5+fbt26UbFixWjnVly8xp07d+a7774z/T1ZsmT06tULgCdPnpiK3ouIiIiIJLQ5c+bQsGHDaH8aNGhAjRo1KFasGCNGjCA8PJxq1arRv39/03Zbtmzh/PnzwKvc1rx5cxo3bmz68+LFi/d6/jFjxtCjRw8cHR2BVzNpXL16leXLl9O9e3dKly5NkyZNOHHiRIxtT58+zYEDB7CwsGDmzJnR7hxKly4dEydOxNLSkr///ts060XkNXz9+vXp0qVLtKn4v/zyS6ZPnw7Anj17OH78eIznzJgxoymzwP/yyC+//MKTJ0+oUKECw4YNizYdYZYsWZg5cyZOTk4cP36cffv2vddrE5kj35Z53secOXN4+fIl7u7uTJkyJVr5h8yZMzNnzhzSpk3L3bt3WbJkSaz7GDVqVLSp+lu3bm3KV8WKFePnn382vZb29vamaTXv3LljOo6oIv/Not7xV6RIEcaMGQPA6tWr8fPzAyAsLIzjx49jMBjw9PSMUTLgq6++Ms1a8qYcWbx48Wgzm7ztNb18+TIA2bJlo0SJEtGW1a5dm4YNG1KjRg1CQkJMj8fFazxhwoRo5RqyZ89O8+bNATh58uQb2ysiklipM05E5CMzGAxUrlwZeNURElXkdCixTQf4uqdPn7J7924AatasGW2ZjY2N6Tk2bdpEQEDAG/fj5ORE0aJF3/nn9QDwNvb29sCrKQw/xJ49e4BX895H7WyMqkWLFsCrTsXnz5/HWP7111/HeCxyypaiRYvGmIrFxsbGVLshttfNwcEh1kLiqVKlolKlSgD8/vvvpscnTJjAmTNn6NatW6ztj3ytQkJCiIiIiLE8X758ODg4xLrt61KmTEmKFCkA6NmzJ3///Xe0ff7444/MmDHDVBAe4uY1jlrgPlJkDQmAZ8+evVf7RURERETi282bNzl58mS0P3///TdXr17F1dWVJk2asGLFCiZNmoSdnZ1puzp16nD58uU3/nm9NtabWFpa0qZNGw4cOMD48eP57rvvTIMD4VUpgqNHj9K4cWNmz54dbdvIa/eiRYuSK1euGPt2dXXFy8uLw4cPkz17dm7evGkaGNesWbNY21OkSBGKFCkCRM8xUZfHNsDyTVk0Upo0aUwlC/74449Y13ldZDYKCwt7r/XfZO/evQA0bNgw1vrlKVKkMJVziDyOqJydnSlcuHCMtkV2aJUtWzbGNlH/DWPLkV9++WW0gY+RypQpQ6ZMmYiIiDC9TlZWVuzevZvTp0/HmmeNRqMpIwYFBcVYDsRaEuNNsmbNCsClS5cYM2YMN2/ejLZ84MCBTJgwgS+++ML02Ie+xunSpYt1Gsrs2bMDxJo7RUQSO9WMExFJAFWrVmXx4sXs2LEDT09PU7jZvn07tra2b5z3PqrNmzcTEhKCtbU1VatWjbG8Vq1arF69mpcvX7JhwwYaN24c637y5cv3xpFq/1VkTYBnz54RERERa6Hn9xEZHN82V3zksvDwcG7dukWBAgWiLY+thkPknW9vGh0Yudz4WrF2gNy5c7+xCHnkXPivhxdLS0tCQkI4fPgw169f5/bt29y8eZNLly5x794903qxvVbvW18h8nl69uzJgAED2LdvH/v27SNFihSUKFGC0qVL8/XXX8eoJxAXr3FsReWj/nARHh7+3scgIiIiIhKfRo0aRd26dYFX19937txh/vz5rFixgvv37+Pm5mbqnIpPjo6OfPfdd6YZJm7dusXhw4fZtWsXBw8exGg0MmnSJPLly2fq/Pnnn38AYu3UiRR1WeTdcfb29tEGy72uQIEC/P3337HOaBFbHnnx4gV37twBYObMmSxevDjW/UauE9mOd0mbNi2XLl3C39//vdaPTUBAgOkOs9dzS1SRGSe2Y35THcDITqfYcqSV1f9+Yo0tR0atPfi63Llz4+PjEyNH2tra8ujRI06dOsXNmzfx8fHh+vXrXLx40XT3XWwDOuHf5cj8+fPz3XffsWnTJn799Vd+/fVXMmbMSMmSJSlTpgxfffVVtJrjcfEax5Yh4X858kM7ZEVEzJE640REEkCRIkXIkCED9+7d49SpUxQpUoTz589z8+ZNKleuHO1C900ip6gMDQ3lyy+/fOu6K1aseGNnXHyIHM0WERHBtWvXcHd3f+c2L168wNfXN1pIjBxRGFsh8UhRX6vYpoaJHF0Zm//SSfi26UMjp5qJeidYaGgoM2bMYPny5Tx58sT0uKWlJe7u7hQqVCjatJave1PH35v8+OOPZM2alQULFvDnn3/y9OlTdu7cyc6dOzEYDHz99dcMHjzY1CkXF69xZOflm8QWRkVEREREEpqFhQWZM2dmyJAhpEmThunTpzNs2DCCg4Np2bLlR21L1qxZyZo1Kw0aNODo0aO0b9+egIAAfvvtN1NnXGSeeN+ZMyKv9d+VLyNzTGzX+rHlkah3fr1pmsSo3vcup2zZsnHgwAGuXbuG0Wh8r5IHvr6+WFpamjqfoh7D2447ctnLly9jPNfbMiT8txwZOYNJbCL/PaPmyAcPHjBmzBi2b98ebcYZe3t7ChYsSHh4eKxTmUaKOjjyfYwbN44vv/yS1atXc/r0ae7cucOaNWtYs2YNtra2/Pjjj/Tu3RsbG5s4eY3flSFFRJIidcaJiCSAyKkqFy5cyPbt2ylSpMi/mqLy0qVLpnoFadKkiVYbLKrg4GCePHnClStXOHnyJEWLFo27g3iL0qVLY2dnR1BQEH/++ed7dcb98ccf9OjRg7Rp0+Ll5UW6dOlMofBt4S1qYIlcPz69fPnyjcsi25k6dWrTYwMHDsTLywtLS0vq16/P559/Tq5cuXBzc8POzo5Dhw69tTPuvyhRogQlSpQgKCiI48ePc+zYMQ4cOMD58+f5448/uHfvHuvXr8dgMJjlaywiIiIi8rF17NiRU6dOcfDgQcaPH0++fPkoWbJknO3//PnzeHp6mgbLvW3Q3RdffEHjxo2ZM2dOtLuKIjuJ3rc+XeS1+9vKFsD/rvff91o/amfVpk2b3ivvvY9vvvmGxYsX8/jxYy5evEi+fPneuc3MmTNZuXIlX3zxBUuWLIl2DG877sg7yxwcHD6ozvn7eluOjGxnZI4MDg6mWbNmeHt74+zsTMOGDSlQoAA5cuQgS5YsWFpaMmnSpLd2xv1bBoOB77//nu+//57Hjx/z119/cfToUfbt28edO3dMs+n079/fbF9jERFzp5pxIiIJJHJqyR07dmA0Gtm2bRsODg6xzgn/usi74pydnfnjjz/Yv39/rH82bdpkmi5jxYoV8XYsr7O3t6dChQoALF68mODg4Hdu89tvvwGvpvyInG8/8g67yI7H2Jw9exZ4FR6yZMnyQe1+H97e3m+80+vixYsA5MyZEwA/Pz/WrVsHwLBhwxg6dCjfffcdefLkMY1U9PX1jbO2hYSE4O3tzenTp4FXoyHLlClDt27d8PLyYuLEicCrztzIIt3m+BqLiIiIiHxsBoOBkSNHkixZMiIiIujTp887O7H+jeTJk3P58mV8fX05fPjwO9ePvNMr6pSIkXW8r169+sbtBgwYQNu2bdm3b5/pWj8wMBBvb+83bnPu3Dngf7XD3iV58uSkSZMGgGvXrr1xvcuXL0ebUvFdPv/8c9P0hfPmzXvn+k+ePGHz5s3A/0oGODk5mfJk5HHFJnLZv6mN/iHe9m926dIl4H85cvfu3Xh7e2NlZcXKlSvp2rUrFStWJFu2bKaBuHGZIwMCAjh37pxpOtFUqVJRtWpVBg0axO7du2nYsCEAGzZsAMz3NRYRMXfqjBMRSSCfffYZGTNm5N69eyxbtow7d+7wzTffvHM6iZCQEDZt2gTAd999F2ux5Ejp0qXjm2++AV7Vo/uQuff/rR49emBnZ8edO3cYPnz4G+eyB1i0aJFpVF/Hjh1Nj5cvXx54Vaj89u3bsW4bWZ/gs88+e++i6R/i4cOHsRYgv3//vqkwdZUqVQC4e/euqeMutppsEREReHl5mf7+obXV9u/fT7Vq1WjTpg0hISExlpcqVSrGc5njaywiIiIikhDSp09Pnz59gFcD68aOHRtn+86cObOpFt2ECRPe2tEXERHBtm3bAKIN1ixXrhwAJ06ciLUO16NHj9iwYQN79+7Fzs6ObNmykS1bNuBV5orNyZMnOXPmDIBpOsz3EdmupUuXxpr1nj9/TrNmzahdu/Ybn/t1lpaW/PzzzwBs3bqV9evXv3HdiIgIBg4cyIsXL7Czs6NVq1amZZEZZ/ny5bHmoqdPn5r2/W+O+UPs37+fBw8exHg8cuYSGxsb04BWHx8f4NWdirF1ZD18+JC9e/cCcVOfe+rUqdSrV48xY8bEWGZhYWG6QzTqc5njaywiYu7UGScikoAqV64MYLpjqXr16u/cZs+ePaZOtXr16r1z/chRbMHBwaa7tD6GTJky4enpicFgYNWqVbRu3Zq///472jqPHj1i5MiRjBo1CoC6devy7bffmpZXqVKF3LlzExwcTOvWrU0jBuHV6L0BAwZw8OBBrKys6Nmz58c5MKBfv34cP37c9HcfHx/at2/Py5cv+eKLLyhTpgzwamRp5MjFefPmERgYaNrm7t27dOnSJdp+oi7/L8qWLUvKlCl58uQJffr0iVaj7sWLF6ZwlSFDBnLlygWY72ssIiIiIpIQvv/+e7744gsAVq1axbFjx+Js356entjb23PlyhV++OEHdu/eHaMjw9vbm59++okTJ07g5uYWrfZ3iRIl+PzzzwkPD6djx47R7nbz8/OjS5cuBAcHU6hQIUqUKAFAly5dAFi5ciVTp06N9nx//fUXnTt3BuCrr76KNnjvXdq0aYODgwMnTpygV69ePH782LTszp07tGnTBn9/f5IlS/av6pdXq1aNGjVqANCnTx+GDRtm6pyKdOXKFVq3bm2a7j9qTWyA1q1b4+joyJUrV+jSpQuPHj0yLbt9+zZt27bl4cOHpE+fnmbNmr132z7Ey5cv+emnn7h3757psb/++gtPT0/g1esZWcc78o7Gp0+fsmjRomgzs5w6dYoWLVqYst6HZkiAmjVrYjAY2Lt3L/PmzYtWo+7u3bvMnj0b+F9nMJjnaywiYu5UM05EJAFVrVqVX3/9lRcvXpAiRQpTJ87bRE5RmS9fPvLmzfvO9UuWLEm2bNm4ceMGK1eupEWLFtHma79w4YKpw+5d8uXLx4ABA95rXYAGDRqQPHlyPD09OXjwIAcPHiRlypS4uroSGBjIzZs3iYiIwMLCgqZNm5pGoUaysrJi5syZtG7dmuvXr1OrVi3c3NxwdHTE29uboKAg7OzsGDJkCMWLF3/vdn2IZMmSYWtrS+PGjcmWLRt2dnZcuXKF8PBw8uTJw7hx40yvb6pUqWjRogXz589n8+bN7Nu3jyxZsvDixQtu3bqF0WikRIkSnDhxgrCwMHx9fXF2dv7PbbOxsWHKlCm0bNmSrVu38vvvv5MlSxYsLCy4ffs2L1++xN7entGjR5vuqDTH11hEREREJKEYDAaGDBlCrVq1CAkJoX///mzatOmtM5K8r8KFCzNr1ix+/vlnrl+/TocOHXBwcCBjxozY2dlx//59/Pz8AMibNy/Tpk3Dyckp2j4mTJhAq1atuHLlCtWrVydHjhxYWFhw48YNQkNDyZgxo2mwJ7zKnP/88w+TJk1ixowZLFq0iGzZsvH48WPu3LkDvKpRFzXHvI+sWbMyefJkunXrxubNm9mxYwc5c+YkNDSUmzdvEhYWhoODA3Pnzo1WU/t9jB8/nrRp07JgwQKWLl3KsmXLcHFxIW3atDx8+JC7d+8Cr+4cGzhwILVr1462febMmZk6dSpdunRhz549lCtXjpw5cxIeHs61a9eIiIjA1dWV6dOnR5sGND65ublx8eJFKlasiLu7Oy9fvuTmzZsA1KhRg7Zt25rWrVChAkWKFOHvv/9m5MiRzJs3j/Tp0/PgwQP8/PwwGAyUKlWKP//8k/v372M0Gj+oJluBAgXo2rUrkyZNYvz48cydO5dMmTIRGBjI7du3CQsLI0uWLKa7FsE8X2MREXOnzjgRkQRUqFAhMmXKhI+PD5UqVcLa2vqt6/v5+XHo0CHg/e6Ki9SgQQNGjRrFzZs3OXLkSLRC5AEBAZw8efK99hNZf+7fqFatGsWKFWP16tUcOnSI69evc/nyZWxsbMiePTtffPEF9evXJ0+ePLFunylTJtauXcvy5cvZvn073t7e+Pr6kiFDBr766isaN278Ueegd3BwYPXq1UyZMoU9e/bg6+tLzpw5qVmzJo0aNcLBwSHa+r169aJgwYIsXryYGzducPnyZVKkSEHJkiWpU6cO3333HU2aNOHYsWP88ccfb3wd3leJEiVYvXo1CxYs4MSJE9y8eRMrKytcXFwoU6YM//d//4erq2u0bcztNRYRERERSUjZs2enXbt2TJ06lZs3bzJjxgy6desWJ/suWbIk27dvZ8OGDRw4cIBLly5x7949goODSZ06NeXLl6dy5crUrFnTNMtGVOnTp2fVqlX89tv/Y+++w6Mo2/aPn5ueEBKkJKEECAGB0KSDVEFUQKWIQAApUgRFepcWOgKCSFNpFnpHQLogAtJVpIQiHUKQlgDp2d8f/LJPIuArsJst+X6O4z0ks7Oz1z7vvTtz7jVzz0Jt2LBBf/31lxITExUYGKjXXntNHTp0MF1hleKDDz5Q5cqV9c033+jgwYM6efKkfHx8VLlyZTVs2FBvv/22nJyefvKsGjVqaP369Zo/f7527dqlc+fOKSkpSblz51aVKlX0/vvvKzAw8Km3azAYNGDAAL311ltasWKFDh48qCtXrigyMlJeXl4qVaqUqlevrmbNmpnurfdPVatW1fr16zVv3jzt3LlT586dk6urq4oWLao33njDdOJoeilRooQmTpyoqVOn6tChQ3JxcVGFChUUGhqqevXqpVnX2dlZ8+fP13fffaf169fr0qVLOnXqlHLkyKF69eqpZcuWKlasmCpWrKg7d+7o8OHDKlu27HPV17lzZxUsWFBLly7VsWPHdOrUKXl4eKho0aKqU6eO3nvvvUeyrq39bwwAts5gTH2tMwAAeKyVK1dq4MCB8vf3188//2ztcgAAAAAANm7AgAFatWqV3nrrLU2cONHa5QAArIh7xgEAAAAAAAAAAAAWQjMOAAAAAAAAAAAAsBCacQAAAAAAAAAAAICFuFi7gKd15coV1apV65Hlo0aN0rvvvmuFigAAAAAAAAAAAIDHMxiNRqO1i3ga27dvV48ePbR161YZDAbT8syZM8vDw8OKlQEAAAAAAAAAAABp2d2VcadOnVJQUJD8/Pyee1tHjhyR0WiUq6urGSoDAAAAYA0JCQkyGAwqXbq0tUuBjSDrAQAAAPbPkbKe3TXjwsPDVbBgQbNsy2g0ys4uDAQAAADwDxzT45/IegAAAID9c6Rjertrxp06dUo5cuRQixYtdP78eeXLl08ffvihqlWr9tTbcnV1ldFoVHBwsAUqBQAAAJAezpw5k2YKeyDlirgSJUpYuRIAAAAAz+ro0aPWLsFs7KoZFx8fr/Pnz8vT01P9+vWTl5eX1q5dq44dO2revHmqXLnyU28zISFBJ06csEC1AAAAANKLm5ubtUsAAAAAAOCx7KoZ5+bmpgMHDsjFxcUUtosXL66zZ89qzpw5z9SMc3V1Ndu0lwAAAADS35kzZ6xdAgAAAAAAT2RXzThJ8vLyemTZiy++qF9++eWZtmcwGB67TQAAAAD2gSkqAQAAAAC2zMnaBTyNkydPqnTp0jp48GCa5X/++SdXtwEAAAAAAAAAAMDm2FUz7sUXX1ShQoUUFhamgwcP6uzZsxo7dqx+++03de7c2drlAQAAAAAAAAAAAGnY1TSVTk5OmjVrliZOnKgePXooKipKISEhmjdvngoXLmzt8gAAAAAAAAAAAIA07KoZJ0lZs2bVmDFjrF0GAAAAAAAAAAAA8H+yq2kqAQAAAAD2ZcaMGXrvvff+dZ3bt2+rd+/eKl++vMqXL68hQ4bowYMH6VQhAAAAAFgWzTgAAAAAgEXMnz9fU6dO/T/X69atmy5dumRaf/fu3QoLC0uHCgEAAADA8uxumkoAAAAAgG27fv26PvnkEx06dEhBQUH/uu6RI0e0f/9+bdiwQcHBwZKkESNGqEOHDurVq5f8/f3To2QAAAAAsBiujAMAAAAAmNWxY8fk6+urtWvXqlSpUv+67sGDB5UjRw5TI06SKlSoIIPBoEOHDlm6VAAAAACwOK6MAwAAAACYVa1atVSrVq3/tO7169eVM2fONMvc3NyUJUsWXbt27ZlrMBqN3HcOAPCfGQwGa5cAB2c0Gq1dAmB3jEajw3w/04wzo+Rko5ycHGNgwLYwtgAAAOCoYmJi5Obm9shyd3d3xcXFPfN2ExISdOLEiecpDQCQQbi6uiokpJhcXJytXQocVGJiko4fP6aEhARrlwLYncdlBXtEM86MnJwMmr5ot65E3rV2KXAguf189VFoFWuXAQAAAFiEh4eH4uPjH1keFxcnLy+vZ96uq6urChYs+DylAQAyCIPBIBcXZ37Xg0Wk/LZXqFAhro4DntKZM2esXYLZ0IwzsyuRd3X+ym1rlwEAAAAAdiEgIEBbt25Nsyw+Pl537tyRv7//M2/XYDA8VzMPAJDx8LseLMnT09PaJQB2x1GmqJQkJ2sXAAAAAADIuMqXL6+IiAhduHDBtGzfvn2SpDJlylirLAAAAIeXnMyVerAMxtajuDIOAAAAAJBukpKSdOvWLWXOnFkeHh4qVaqUypQpo549e2r48OF68OCBhg0bpoYNGz7XlXEAAAD4d9x2CZbAbZcej2YcAAAAACDdXLt2TbVr19bYsWPVuHFjGQwGTZs2TWFhYWrTpo3c3d31xhtvaODAgdYuFQAAwOExPSuQPmjGAQAAAAAsZty4cWn+zpMnj8LDw9Msy5Ytm6ZOnZqeZQEAAABAuuGecQAAAAAAAAAAAICF0IwDAAAAAACASXKy0dolwIExvgAAGRHTVAIAAAAAAMDEycmg6Yt260rkXWuXAgeT289XH4VWsXYZAACkO5pxAAAAAAAASONK5F2dv3Lb2mUAAAA4BKapBAAAAAAAAAAAACyEZhwAAAAAAAAAAABgITTjAAAAAAAAAAAAAAuhGQcAAAAAAAAAAABYCM04AAAAAAAAAAAAwEJoxgEAAAAAAAAAAAAWQjMOAAAAAAAAAAAAsBCacQAAAAAAAAAAAICF0IwDAAAAAAAAAAAALIRmHAAAAAAAAAAAAGAhNOMAAAAAAAAAAAAAC6EZBwAAAAAAAAAAAFgIzTgAAAAAAAAAAADAQmjGAQAAAAAAAAAAABZCMw4AAAAAAAAAAACwEJpxAAAAAAAAAAAAgIXQjAMAAAAAAAAAAAAshGYcAAAAAAAAAAAAYCE04wAAAAAAAAAAAAALoRkHAAAAAAAAAAAAWAjNOAAAAAAAAAAAAMBCaMYBAAAAAAAAAAAAFkIzDgAAAAAAAAAAALAQmnEAAAAAAAAAAACAhdCMAwAAAAAAAAAAACyEZhwAAAAAAAAAAABgITTjAAAAAAAAAAAAAAuhGQcAAAAAAAAAAABYCM04AAAAAAAAAAAAwELsthl37tw5lS5dWitXrrR2KQAAAAAAAAAAAMBj2WUzLiEhQX369NGDBw+sXQoAAAAAAAAAAADwRHbZjPviiy+UKVMma5cBAAAAAAAAAAAA/Cu7a8YdOHBAS5Ys0fjx461dCgAAAAAAAAAAAPCvXKxdwNOIiopSv379NHjwYOXMmdMs2zQajWaZ7tJgMMjT09MMFQGPFxMTI6PRaO0yAAAAbI7RaJTBYLB2GQAAAAAAPJZdNeOGDx+ul156SW+99ZbZtpmQkKATJ04893Y8PT0VEhJihoqAxzt37pxiYmKsXQYAAIBNcnNzs3YJAAAAAAA8lt0041avXq2DBw/qhx9+MOt2XV1dVbBgwefeDmfiwtKCgoK4Mg4AAOAxzpw5Y+0SAAAAAAB4Irtpxq1YsUI3b95UzZo10ywfNmyY5syZo/Xr1z/Tdg0Gg7y8vMxQIWBZTIMKAADweJwYBwAAAACwZXbTjJs4caJiY2PTLHvttdfUrVs31atXz0pVAQAAAAAAAAAAAE9mN804f3//xy7Pli2bcufOnc7VAAAAAAAAAAAAAP83J2sXAAAAAABwLMnJyZo6daqqVaumUqVK6f3339eFCxeeuP6NGzfUq1cvVaxYURUrVlT37t0VERGRjhUDAAAAgOXYdTMuPDxcjRs3tnYZAAAAAIBUZsyYocWLF2vUqFFasmSJDAaDOnbsqPj4+Meu37NnT127dk3z5s3TvHnzFBERoQ8//DCdqwYAAAAAy7DrZhwAAAAAwLbEx8dr7ty5+vjjj1WjRg0VKVJEkydP1vXr17Vly5ZH1o+KitKBAwfUsWNHhYSEKCQkRJ06ddKxY8d0+/ZtK7wDAAAAADAvu7lnHAAAAADA9p08eVL3799XpUqVTMt8fHwUEhKiAwcOqH79+mnWd3d3l5eXl1avXq0KFSpIktasWaP8+fPL19f3meswGo168ODBMz8fyKgMBoM8PT2tXQYcXExMjIxGo7XLMGHcIz0w7pHRmGPMG41GGQwGM1VkXTTjAAAAAABmk3Kvt5w5c6ZZ7ufnp2vXrj2yvru7u0aPHq0RI0aoXLlyMhgMypEjh77//ns5OT37ZC4JCQk6ceLEMz8fyKg8PT0VEhJi7TLg4M6dO6eYmBhrl2HCuEd6YNwjozHXmHdzczNDNdZHMw4AAAAAYDYpgfufodnd3V137959ZH2j0ajw8HCVLl1aHTp0UFJSkiZPnqyPPvpIixYtkre39zPV4erqqoIFCz7Tc4GMzFHOPodtCwoKsrkrhABLY9wjozHHmD9z5oyZqrE+mnEAAAAAALPx8PCQ9PDecSn/lqS4uLjHToW0fv16LVy4UD/99JOp8TZr1iy98sorWrFihdq0afNMdRgMBnl5eT3TcwEAlsXUeMiIGPfIaMwx5h2pafzsc34AAAAAAPAPKdNTRkZGplkeGRmpgICAR9Y/dOiQgoKC0lwB5+vrq6CgIJ0/f96itQIAAABAeqAZBwAAAAAwmyJFisjb21v79u0zLYuKitLx48dVrly5R9bPmTOnLly4oLi4ONOymJgYXb58Wfny5UuXmgEAAADAkmjGAQAAAADMxs3NTa1atdLEiRO1bds2nTx5Uj179lRAQIDq1KmjpKQk3bhxQ7GxsZKkhg0bSpJ69OihkydPmtZ3c3NT48aNrfhOAAAAAMA8aMYBAAAAAMyqW7duatKkiQYPHqzQ0FA5Oztrzpw5cnNz07Vr11S1alVt2LBBkuTn56eFCxfKaDSqTZs2ateunVxdXbVo0SL5+PhY+Z0AAAAAwPNzsXYBAAAAAADH4uzsrL59+6pv376PPJYnTx6Fh4enWRYcHKxZs2alV3kAAAAAkK64Mg4AAAAAAAAAAACwEJpxAAAAAAAAAAAAgIXQjAMAAAAAAAAAAAAshGYcAAAAAAAAAAAAYCE04wAAAAAAAAAAAAALoRkHAAAAAAAAAAAAWAjNOAAAAAAAAAAAAMBCaMYBAAAAAAAAAAAAFkIzDgAAAAAAAAAAALAQmnEAAAAAAAAAAACAhdCMAwAAAAAAAAAAACyEZhwAAAAAAAAAAABgITTjAAAAAAAAAAAAAAuhGQcAAAAAAAAAAABYCM04AAAAAAAAAAAAwEJoxgEAAAAAAAAAAAAWQjMOAAAAAAAAAAAAsBCacQAAAAAAAAAAAICF0IwDAAAAAAAAAAAALIRmHAAAAAAAAAAAAGAhNOMAAAAAAAAAAAAAC6EZBwAAAAAAAAAAAFgIzTgAAAAAAAAAAADAQmjGAQAAAAAAAAAAABZCMw4AAAAAAAAAAACwEJpxAAAAAAAAAAAAgIXQjAMAAAAAAAAAAAAshGYcAAAAAAAAAAAAYCE04wAAAAAAAAAAAAALoRkHAAAAAAAAAAAAWAjNOAAAAAAAAAAAAMBCaMYBAAAAQAYWHx+vOXPmqHnz5qpWrZoOHjyoY8eOaeTIkbp586a1ywMAAAAAu+di7QIAAAAAANYRFxenNm3a6LfffpO7u7vi4+OVkJCgv//+WwsWLNAvv/yihQsXKlu2bNYuFQAAAADsFlfGAQAAAEAGNWvWLP3+++8aPXq0tm3bJqPRKEl6/fXXNWzYMF2+fFlffvmllasEAAAAAPtGMw4AAAAAMqgNGzaoQYMGeuedd+Ts7GxabjAYFBoaqsaNG2vHjh3WKxAAAAAAHIDdNeNu3rypvn37qlKlSipdurQ6deqkM2fOWLssAAAAALA7V69e1UsvvfTEx0uWLKmIiIj0KwgAAAAAHJDdNeO6dOmiS5cu6euvv9by5cvl4eGhtm3bKiYmxtqlAQAAAIBdyZw5s27evPnExy9evKjMmTOnY0UAAAAA4Hjsqhl3+/Zt5cmTRyNHjlSJEiUUHBysDz/8UDdu3NDp06etXR4AAAAA2JVKlSpp2bJlio6OfuSxS5cuafHixSpfvrwVKgMAAAAAx+Fi7QKexgsvvKDPPvvM9Pfff/+tOXPmKCAgQAULFnymbRqNRj148OC5azMYDPL09Hzu7QBPEhMTI6PRaO0yAAAAbI7RaJTBYLB2GXbp448/VpMmTdSgQQPVqFFDBoNB27Zt07Zt27Ry5UolJSWpc+fO1i4TAAAAAOyaXTXjUhsyZIiWLl0qNzc3zZw5U15eXs+0nYSEBJ04ceK56/H09FRISMhzbwd4knPnzjEdKwAAwBO4ublZuwS7FBQUpHnz5mnQoEFatGiRJOn777+XJOXOnVujRo1SkSJFrFkiAAAAANg9u23GtWnTRs2aNdOiRYv00UcfaeHChSpWrNhTb8fV1fWZr6pLjTNxYWlBQUFcGQcAAPAYZ86csXYJdis+Pl4lS5bUunXrFB4ernPnzik5OVl58uRR8eLF5eRkV3c2sJjkZKOcnMh8MD/GFgAAQMZgt824lAbayJEj9dtvv+n777/X2LFjn3o7BoPhma+qA9IT06ACAAA8HifGPbuGDRuqadOmatu2rQoXLqzChQtbuySb5ORk0PRFu3Ul8q61S4EDye3nq49Cq1i7DAAAAKQDu2rG3bx5U3v37lXdunXl7OwsSXJyclJwcLAiIyOtXB0AAAAA2JdLly5Z5OTE5ORkTZs2TcuWLVNUVJTKli2rYcOGKV++fI9dPyEhQVOnTtXq1asVHR2t4sWL65NPPlHRokXNXtuzuhJ5V+ev3LZ2GQAAAADskF3NORIZGanevXtr//79pmUJCQk6fvy4goODrVgZAAAAANifIkWK6NChQ2bf7owZM7R48WKNGjVKS5YskcFgUMeOHRUfH//Y9YcPH67ly5dr5MiRWrFihbJkyaKOHTsqOjra7LUBAAAAQHqzqyvjihQpoqpVqyosLEyjRo2Sj4+PZs2apaioKLVt29ba5QEAAACAXWnXrp0GDx6sCxcuqGbNmsqePbtcXB6NiQ0bNvzP24yPj9fcuXPVt29f1ahRQ5I0efJkVatWTVu2bFH9+vXTrH/p0iUtX75cX375pWrWrClJGjNmjBo2bKg///xTlStXfub3BwAAAAC2wK6acQaDQVOmTNGkSZPUo0cPRUdHq1y5clqwYIFy5cpl7fIAAAAAwK706tVLkvTbb7/pt99+k5T2HnxGo1EGg+GpmnEnT57U/fv3ValSJdMyHx8fhYSE6MCBA48043755Rf5+PioevXqadbfvn37M7yj/zEajXrw4MFzbUN6+L8H92+GJcXExMhoNFq7DBPGPNID4x4ZEeMeGY05xnxKHnEEdtWMk6TMmTNr+PDhGj58uLVLAQAAAAC7NnbsWLNvMyIiQpKUM2fONMv9/Px07dq1R9Y/f/68AgMDtXnzZn311Ve6fv26QkJCNGDAgOe6HUFCQoJOnDjxzM9P4enpqZCQkOfeDvAk586dU0xMjLXLMGHMIz0w7pERMe6R0ZhrzLu5uZmhGuuzu2YcAAAAAMA8GjVqZPZtpgTuf4Zmd3d33b1795H17927p4sXL2rGjBnq16+ffHx8NHPmTLVo0UIbNmxQtmzZnqkOV1dXFSxY8Jmem5qjnIkL2xUUFGRzV0oAlsa4R0bEuEdGY44xf+bMGTNVY3004wAAAAAgg7t06ZI2b96sy5cvy83NTTlz5lSdOnWUO3fup96Wh4eHpIf3jkv5tyTFxcU9diokV1dXRUdHa/LkyaYr4SZPnqwaNWpo1apV6tChwzO9J4PBIC8vr2d6LpCemCIMGRHjHhkR4x4ZjTnGvCM1jWnGAQAAAEAGNn/+fE2cOFGJiYlplk+cOFG9evXS+++//1TbS5meMjIyUnnz5jUtj4yMVJEiRR5ZPyAgQC4uLmmmpPTw8FBgYKAuX778VK8NAAAAALbIyZovHhsbq6tXr1qzBAAAAADIsH7++WeNGzdOefPm1aeffqrVq1drxYoVpmUTJkzQ7t27n2qbRYoUkbe3t/bt22daFhUVpePHj6tcuXKPrF+uXDklJibq6NGjpmWxsbG6dOmS8uXL9+xvDgAAAABshFmbcY0aNdLPP/+cZllCQoK2bdum27dvP7L+5s2bVbt2bXOWAAAAAAD4j+bMmaN8+fJp+fLlevvtt1WkSBEVK1ZMDRs21PLly5U3b17Nmzfvqbbp5uamVq1aaeLEidq2bZtOnjypnj17KiAgQHXq1FFSUpJu3Lih2NhYSQ+bcS+//LL69++vgwcP6syZM+rXr5+cnZ3VoEEDS7xtAAAAAEhXZm3GnThx4pEbct+7d09du3bVyZMnzflSAAAAAIDn9Oeff6pRo0aPvbeal5eXGjVqlOaKtf+qW7duatKkiQYPHqzQ0FA5Oztrzpw5cnNz07Vr11S1alVt2LDBtP4XX3yhChUqqGvXrmrSpInu3bunb7/9VlmzZn2u9wcAAAAAtiBd7hlnNBrT42UAAAAAAE8hMTFRmTJleuLjXl5epivYnoazs7P69u2rvn37PvJYnjx5FB4enmaZt7e3hg8fruHDhz/1awEAAACArbPqPeMAAAAAANYTFBSk7du3P/Hxbdu2cd82AAAAAHhONOMAAAAAIIN65513tHfvXg0aNEjXr183Lb9+/boGDhyo/fv3q1GjRlasEAAAAADsX7pMUwkAAAAAsD0tW7bUnj17tHLlSq1atUre3t4yGAyKjo6W0WhUjRo11KZNG2uXCQAAAAB2jWYcAAAAAGRQTk5OmjFjhtasWaONGzfq0qVLMhqNKlOmjF5//XU1aNBATk5MqAIAAAAAz4NmHAAAAABkYAaDQQ0aNFDDhg1NyyIjI5U9e3YacQAAAABgBmZvxi1dulR79uwx/R0fHy+DwaA5c+Zo7dq1ada9fPmyuV8eAAAAAPAUli1bpqlTp2rhwoUKDAyUJE2ePFk7duzQsGHD9MYbb1i5QgAAAACwb2Zvxh04cEAHDhx4ZPkvv/zy2PUNBoO5SwAAAAAA/AebN2/WkCFDlDdvXiUnJ5uWv/zyyzp69Kh69uwpX19fVa5c2YpVAgAAAIB9M2sz7ttvvzXn5gAAAAAAFjR37lyVKFFC33//vdzd3U3L33rrLb3++utq0aKFZs6cSTMOAAAAAJ6DWZtxFSpUeOrn3L1715wlAAAAAAD+ozNnzqh3795pGnEp3Nzc1LBhQ02dOtUKlQEAAACA47Da3biPHDmi/v37q0aNGtYqAQAAAAAyNGdnZ0VFRT3x8ZiYGCUmJqZjRQAAAADgeMx+z7h/c//+fa1du1aLFy/WqVOnZDQa5ebmlp4lAAAAAAD+v+LFi2v58uV677335OXlleax2NhYrVq1SsWLF7dSdQAAAADgGNKlGXfy5EktWrRI69at04MHD2Q0GpU1a1aFhoaqRYsW6VECAAAAAOAf2rdvr/bt26tJkyYKDQ1VgQIFZDAYdO7cOS1ZskTnzp3TgAEDrF0mAAAAANg1izXj4uPjtX79ei1evFh//PGHjEajJMlgMKhTp07q2rUrV8UBAAAAgBW9/PLLGjFihMaOHavRo0fLYDBIkoxGozw9PTV8+HBVr17dylUCAAAAgH0zezPu3LlzWrx4sVavXq2oqCgZjUblzp1b9evXV+nSpdWlSxeVKlWKRhwAAAAA2IB3331X9erV0549e3T58mUlJCQoT548qlKlinx9fa1dHgAAAADYPbM249q0aaP9+/fLaDTK399fb7/9turXr6+XXnpJknTlyhVzvhwAAAAAwAwyZcqkOnXqWLsMAAAAAHBIZm3G7du3T5kyZVLHjh3Vtm1beXh4mHPzAAAAAAAziImJ0cmTJ1W6dGnTsoSEBC1atEj79u2Th4eH6tatq1dffdWKVQIAAACAY3Ay58YaNGig5ORkff7556pQoYLef/99LVu2THfv3jXnywAAAAAAntGWLVv0yiuvqFWrVqZlRqNRnTp10tixY7Vt2zatX79eH3/8sYYOHWrFSgEAAADAMZi1GTd+/Hj98ssvCgsLU0hIiPbs2aOhQ4eqSpUq6ty5szZu3Gi6ITgAAAAAIH2dOXNGPXr0kMFgUKtWrZSUlCRJWrZsmfbu3ausWbNq8eLFOnz4sHr27Klly5Zpy5YtVq4aAAAAAOybWaeplB7ea6Bp06Zq2rSp/vrrLy1fvlxr167Vjh07tHPnTknSihUrFBAQoGLFipn75QEAAAAATzBv3jxlzpxZq1evlr+/v2n5kiVLZDAY9OGHH5ru+d2pUyft2bNHS5cu5X5yAAAAAPAczHpl3D8VKFBA/fr1086dOzVjxgzVqlVLzs7O2r59u5o0aaKmTZtq9erVliwBAAAAAPD/7du3T40bN07TiLt9+7aOHz8ug8GgunXrplm/Ro0aOnbsWHqXCQAAAAAOxexXxj2Os7OzatWqpVq1aunWrVtas2aNVq5cqT/++ENHjx5Vw4YN06MMAAAAAMjQbty4oaCgoDTLDh06JKPRqBdffFFZs2ZN85ivr6+io6PTs0QAAAAAcDjp0oxLLWvWrGrXrp3atWunP/74QytXrkzvEgAAAAAgQ3J1dVVsbGyaZQcOHJAkVahQ4ZH1b9y4IR8fn3SpDQAAAAAclVmbca1btzbn5gAAAAAAZhQUFKSjR4+mWbZ9+3YZDAZVrVr1kfW3bdumAgUKpFd5AAAAAOCQzNqM279/vwwGgyTJaDT+p+ekrA8AAAAAsKy6detq8uTJqlmzpmrWrKnvv/9ely5dUo4cOVSlSpU0637//fc6evSoBgwYYKVqAQAAAMAxmLUZlytXLl29elXZs2fXG2+8ofr166t06dLmfAkAAAAAwDNq1aqVfvzxR/Xu3du0zNnZWSNGjJCLy8N4uGnTJn377bc6fPiwgoKCFBoaaq1yAQAAAMAhmLUZt337dv3+++/asGGDNm7cqAULFihnzpyqX7++6tevryJFipjz5QAAAAAAT8HNzU3ffvutFixYoIMHD8rb21uhoaEqW7asaZ0///xThw4dUtWqVTVu3Di5ublZsWIAAAAAsH9mbcZJUqlSpVSqVCkNHDhQBw4c0Pr167Vy5UrNnj1b+fLl05tvvql69epx3wEAAAAAsAJPT0916NBBHTp0eOzj7733nt577z35+fmlc2UAAAAA4JjM3oxLrXz58ipfvryGDh2qvXv3asOGDfruu+80ffp0FSlSRPXr11e9evWUK1cuS5YBAAAAAPiPaMIBAAAAgHk5pcuLODmpSpUqGj16tHbv3q1Zs2bJ399fkyZN0quvvpoeJQAAAAAAAAAAAADpzqJXxv3TrVu3tGXLFv344486cOCAjEajAgIC0rMEAAAAAAAAAAAAIN1YvBl369Ytbd68WRs3btTBgweVmJgoPz8/tWjRQvXq1VPp0qUtXQIAAAAAAAAAAABgFRZpxj2uAZc9e3Y1a9ZMdevWVdmyZWUwGCzx0gAAAAAAAAAAAIDNMGszbtGiRaYGXFJSkrJmzap33nlH9erVU4UKFWjAAQAAAIAVGY1GRUVFydfXN83yq1evKleuXFaqCgAAAAAcm1mbcWFhYTIYDMqbN6/q1q2rSpUqydnZWZJ08ODBJz6vfPny5iwDAAAAAPAP+/btU/fu3XX37l0VLVpUo0aNUkhIiCSpdu3aOnHihJUrBAAAAADHZPZpKo1Goy5cuKAvv/xSX3755X96DqEPAAAAACxr3Lhxevnll1W8eHHNmTNHrVu31nfffaeiRYvKaDRauzwAAAAAcFhmbcZ17drVnJsDAAAAAJjJ+fPntWjRInl4eKhKlSpq2bKlOnXqpCVLlnBLAQAAAACwIJpxAAAAAJAB+Pr6av/+/apevboKFy6sL774Qh988IHatWtn7dIAAAAAwKE5WbuAp3Hnzh0NHTpU1atXV5kyZRQaGvqv96IDAAAAADzUokULffDBB9q/f78kqXLlyvr8888VGRlp5coAAAAAwLGZ/Z5xltSrVy/dvHlTn332mbJmzaqFCxeqffv2WrlypYKDg61dHgAAAADYrE6dOunFF19Mk51eeeUVLV++XF9//bUVKwMAAAAAx2Y3V8ZduHBBu3fv1rBhw1SuXDkVKFBAn3zyifz9/bVu3TprlwcAAAAANq9mzZrKli1bmmXBwcEaN27cE5+zcOFCS5cFAAAAAA7Nbq6Me+GFF/TVV1+pePHipmUGg0FGo1F37961YmUAAAAAYD+MRqN++uknHThwQJJUokQJ1a1bVwaDIc16169f16BBg7Rnzx61aNHCGqUCAAAAgEOwm2acj4+PatSokWbZjz/+qIsXL6pq1arPvF2j0agHDx48b3kyGAzy9PR87u0ATxITEyOj0WjtMgAAAGyO0Wh8pJGEx7t37546d+6sQ4cOmY4tDQaD5s6dqzlz5sjX11eStGHDBoWFhenu3bsqUKCANUsGAAAAALtnN824fzp06JAGDRqk2rVrq1atWs+8nYSEBJ04ceK56/H09FRISMhzbwd4knPnzikmJsbaZQAAANgkNzc3a5dgF2bMmKGDBw+qcuXKatKkiby8vLR582atWrVKn332mcLCwvTpp59q3rx5kqTWrVurT58+T/06ycnJmjZtmpYtW6aoqCiVLVtWw4YNU758+f7P5/7www/q06ePtm3bpjx58jz1awMAAACArbHLZtzWrVvVp08flSpVSp999tlzbcvV1VUFCxZ87po4ExeWFhQUxJVxAAAAj3HmzBlrl2A3du7cqZIlS5qabZL0yiuvKEuWLFq6dKmCgoI0d+5cBQQEaPz48apYseIzvc6MGTO0ePFijR07Vv7+/powYYI6duyodevW/Wvj9MqVKwoLC3um1wQAAAAAW2V3zbjvv/9eo0ePVp06dTRx4sTnPgPWYDDIy8vLTNUBlsM0qAAAAI/HiXH/XUREhLp06fLI8gYNGmjevHn67LPPVKVKFX322WemKSufVnx8vObOnau+ffuabjUwefJkVatWTVu2bFH9+vUf+7zk5GT17dtXxYoV06+//vpMrw0AAAAAtsjJ2gU8jYULF2rkyJFq2bKlpkyZwlQ0AAAAAPAU7t+/Lz8/v0eW58iRQ5IUEhKir7766pkbcZJ08uRJ3b9/X5UqVTIt8/HxUUhIiA4cOPDE582aNUsJCQn64IMPnvm1AQAAAMAW2c2VcefOndOYMWNUp04dffDBB7p586bpMQ8PD2XOnNmK1QEAAACAfXjclYROTg/P02zVqpWcnZ2fa/sRERGSpJw5c6ZZ7ufnp2vXrj32OX/88Yfmzp2r5cuX6/r168/1+imMRqMePHjw3NsxGAzMUgGLiomJsalbEjDmkR4Y98iIGPfIaMwx5o1Go8PMhGI3zbhNmzYpISFBW7Zs0ZYtW9I81qhRI40bN85KlQEAAACAY8iWLdtzbyMmJkaSHpnJxN3dXXfv3n1k/QcPHqhPnz7q06eP8ufPb7ZmXEJCgk6cOPHc2/H09FRISIgZKgIe79y5c6bPjS1gzCM9MO6RETHukdGYa8w7ygyJdtOM69y5szp37mztMgAAAAAA/8LDw0PSw3vHpfxbkuLi4h579vWoUaOUP39+NW/e3Kx1uLq6qmDBgs+9HUc5Exe2KygoyOaulAAsjXGPjIhxj4zGHGP+zJkzZqrG+uymGQcAAAAAeH4HDx5UUlJSmmX379+XJO3evfuxV6Y1bNjwP28/ZXrKyMhI5c2b17Q8MjJSRYoUeWT9FStWyM3NTaVLl5YkU21vvvmm3n77bY0YMeI/v3ZqBoNBXl5ez/RcID0xRRgyIsY9MiLGPTIac4x5R2oa04wDAAAAgAxk6dKlWrp06WMfmzNnTpq/U+7R8DTNuCJFisjb21v79u0zNeOioqJ0/PhxtWrV6pH1N2/enObv33//XX379tVXX32l4ODg//y6AAAAAGCraMYBAAAAQAbRtWtXi7+Gm5ubWrVqpYkTJypr1qzKnTu3JkyYoICAANWpU0dJSUm6deuWMmfOLA8PD+XLly/N8yMiIiRJuXLlMss97AAAAADA2mjGAQAAAEAGkR7NOEnq1q2bEhMTNXjwYMXGxqp8+fKaM2eO3NzcdPnyZdWuXVtjx45V48aN06UeAAAAALAmmnEAAAAAALNydnZW37591bdv30cey5Mnj8LDw5/43IoVK/7r4wAAAABgb5ysXQAAAAAAAAAAAADgqGjGAQAAAAAAAAAAABZCMw4AAAAAAAAAAACwEJpxAAAAAAAAAAAAgIXQjAMAAAAAAAAAAAAshGYcAAAAAAAAAAAAYCE04wAAAAAAAAAAAAALoRkHAAAAAAAAAAAAWAjNOAAAAAAAAAAAAMBCaMYBAAAAAAAAAAAAFkIzDgAAAAAAAAAAALAQmnEAAAAAAAAAAACAhdCMAwAAAAAAAAAAACyEZhwAAAAAAAAAAABgITTjAAAAAAAAAAAAAAuhGQcAAAAAAAAAAABYCM04AAAAAAAAAAAAwEJoxgEAAAAAAAAAAAAWQjMOAAAAAAAAAAAAsBCacQAAAAAAAAAAAICF0IwDAAAAAAAAAAAALIRmHAAAAAAAAAAAAGAhNOMAAAAAAAAAAAAAC6EZBwAAAAAAAAAAAFgIzTgAAAAAAAAAAADAQmjGAQAAAAAAAAAAABZCMw4AAAAAAAAAAACwEJpxAAAAAAAAAAAAgIXQjAMAAAAAAAAAAAAshGYcAAAAAAAAAAAAYCE04wAAAAAAAAAAAAALoRkHAAAAAAAAAAAAWAjNOAAAAAAAAAAAAMBCaMYBAAAAAAAAAAAAFkIzDsAzS042WrsEODDGFwAAAAAAAABH4GLtAgDYLycng6Yv2q0rkXetXQocTG4/X30UWsXaZQAAAAAAAADAc6MZB+C5XIm8q/NXblu7DAAAAAAAAAAAbBLTVAIAAAAAAAAAAAAWQjMOAAAAAAAAAAAAsBCacQAAAAAAAAAAAICF2HUzbsaMGXrvvfesXQYAAAAAAAAAAADwWHbbjJs/f76mTp1q7TIAAAAAAAAAAACAJ3KxdgFP6/r16/rkk0906NAhBQUFWbscAAAAAAAAAAAA4Ins7sq4Y8eOydfXV2vXrlWpUqWsXQ4AAAAA4B+Sk5M1depUVatWTaVKldL777+vCxcuPHH906dPq1OnTqpYsaIqV66sbt266erVq+lYMQAAAABYjt1dGVerVi3VqlXLbNszGo168ODBc2/HYDDI09PTDBUBjxcTEyOj0WjtMkwY80gPtjbuAQC2yWg0ymAwWLsMpDJjxgwtXrxYY8eOlb+/vyZMmKCOHTtq3bp1cnNzS7Pu7du31a5dO5UvX17ff/+94uLiNH78eHXo0EGrVq2Su7u7ld4FAAAAAJiH3TXjzC0hIUEnTpx47u14enoqJCTEDBUBj3fu3DnFxMRYuwwTxjzSg62NewCA7fpngwfWEx8fr7lz56pv376qUaOGJGny5MmqVq2atmzZovr166dZf+vWrYqJidG4ceNMjbcJEyaoRo0aOnz4sCpXrpzu7wEAAAAAzCnDN+NcXV1VsGDB594OZ+LC0oKCgmzqCiHGPNKDrY17AIBtOnPmjLVLQConT57U/fv3ValSJdMyHx8fhYSE6MCBA4804ypXrqzp06c/9gq4u3fvPnMdzIICe2Frs0Ew5pEeGPfIiBj3yGjMMeYdaRaUDN+MMxgM8vLysnYZwP+JnSMyIsY9AOC/cJRw5igiIiIkSTlz5kyz3M/PT9euXXtk/Tx58ihPnjxpln355Zdyd3dX+fLln7kOZkGBvbC12SAY80gPjHtkRIx7ZDTmGvOOMgtKhm/GAQAAAADMJyVw/zM0u7u7/6cr3b799lstXLhQAwcOVLZs2Z65DmZBgb2wtdkgGPNID4x7ZESMe2Q05hjzjjQLCs04AAAAAIDZeHh4SHp477iUf0tSXFzcv171bjQa9fnnn2vmzJn64IMP1LZt2+eqg1lQYC+YDQIZEeMeGRHjHhmNOca8IzWNnaxdAAAAAADAcaRMTxkZGZlmeWRkpAICAh77nISEBPXt21ezZs1Sv3791KtXL4vXCQAAAADpxa6vjBs3bpy1SwAAAAAApFKkSBF5e3tr3759yps3ryQpKipKx48fV6tWrR77nH79+mnLli2aNGmS6tevn57lAgAAAIDF2XUzDgAAAABgW9zc3NSqVStNnDhRWbNmVe7cuTVhwgQFBASoTp06SkpK0q1bt5Q5c2Z5eHho5cqV2rBhg/r166cKFSroxo0bpm2lrAMAAAAA9oxpKgEAAAAAZtWtWzc1adJEgwcPVmhoqJydnTVnzhy5ubnp2rVrqlq1qjZs2CBJWrdunSTp008/VdWqVdP8X8o6AAAAAGDPuDIOAAAAAGBWzs7O6tu3r/r27fvIY3ny5FF4eLjp77lz56ZnaQAAAACQ7rgyDgAAAAAAAAAAALAQmnEAAAAAAAAAAACAhdCMAwAAAAAAAAAAACyEZhwAAAAAAAAAAABgITTjAAAA8K+Sk43WLgEOirEFAAAAAMgIXKxdAAAAAGybk5NB0xft1pXIu9YuBQ4kt5+vPgqtYu0yAAAAAACwOJpxAAAA+D9dibyr81duW7sMAAAAAAAAu8M0lQAAAAAAAAAAAICF0IwDAAAAAAAAAAAALIRmHAAAAAAAAAAAAGAhNOMAAAAAAAAAAAAAC6EZBwAAAAAAAAAAAFgIzTgAAAAAAAAAAADAQmjGAQAAAAAAAAAAABZCMw4AAAAAAAAAAACwEJpxAAAAAAAAAAAAgIXQjAMAAAAAAAAAAAAshGYcAAAAAAAAAAAAYCE04wAAAAAAAAAAAAALoRkHAAAAAAAAAAAAWAjNOAAAAAAAAAAAAMBCaMYBAAAAAAAAAAAAFkIzDgAAAAAAAAAAALAQmnEAAAAAAAAAAACAhdCMAwAAAAAAAAAAACyEZhwAAAAAAAAAAABgITTjAAAAAAAAAAAAAAuhGQcAAAAAAAAAAABYCM04AAAAAAAAAAAAwEJoxgEAAAAAAAAAAAAWQjMOAAAAAAAAAAAAsBCacQAAAAAAAAAAAICF0IwDAAAAAAAAAAAALIRmHAAAAAAAAAAAAGAhNOMAAAAAAAAAAAAAC6EZBwAAAAAAAAAAAFgIzTgAAAAAAAAAAADAQmjGAQAAAAAAAAAAABZCMw4AAAAAAAAAAACwEJpxAAAAAAAAAAAAgIXQjAMAAAAAAAAAAAAshGYcAAAAAAAAAAAAYCF214xLTk7W1KlTVa1aNZUqVUrvv/++Lly4YO2yAAAAAAD/39Pmttu3b6t3794qX768ypcvryFDhujBgwfpWDEAAAAAWI7dNeNmzJihxYsXa9SoUVqyZIkMBoM6duyo+Ph4a5cGAAAAANDT57Zu3brp0qVLmj9/vqZOnardu3crLCwsnasGAAAAAMuwq2ZcfHy85s6dq48//lg1atRQkSJFNHnyZF2/fl1btmyxdnkAAAAAkOE9bW47cuSI9u/fr7Fjx6pYsWKqXLmyRowYoTVr1uj69etWeAcAAAAAYF4u1i7gaZw8eVL3799XpUqVTMt8fHwUEhKiAwcOqH79+k+1vYSEBBmNRv3xxx9mqc9gMKh+hRxKSs5mlu0BkuTs5KSjR4/KaDRau5RHMOZhKbY87oGMiO97WII5v+sTEhJkMBjMUBXM4Wlz28GDB5UjRw4FBwebllWoUEEGg0GHDh1SvXr1nroGsh7sgS0f8zLmYSmMe2REjHtkNGS9x7OrZlxERIQkKWfOnGmW+/n56dq1a0+9vZT/J5rz/5k+3h5m2xaQmq1+6TDmYUm2Ou6BjIjve1iKOb7rDQYD+wwb8rS57fr164+s6+bmpixZsjxTzpPIerAvtvr9xZiHJTHukREx7pHRkPXSsqtmXExMjKSHwSw1d3d33b1796m3V7p0abPUBQAAAAB46GlzW0xMzCPrpqwfFxf3TDWQ9QAAAADYEru6Z5yHx8Mu/T9v+h0XFydPT09rlAQAAAAASOVpc5uHh8cj66as7+XlZZkiAQAAACAd2VUzLmXqksjIyDTLIyMjFRAQYI2SAAAAAACpPG1uCwgIeGTd+Ph43blzR/7+/pYrFAAAAADSiV0144oUKSJvb2/t27fPtCwqKkrHjx9XuXLlrFgZAAAAAEB6+txWvnx5RURE6MKFC6ZlKc8tU6aM5QsGAAAAAAuzq3vGubm5qVWrVpo4caKyZs2q3Llza8KECQoICFCdOnWsXR4AAAAAZHj/V25LSkrSrVu3lDlzZnl4eKhUqVIqU6aMevbsqeHDh+vBgwcaNmyYGjZsyJVxAAAAAByCwWg0Gq1dxNNISkrSZ599ppUrVyo2Nlbly5fX0KFDlSdPHmuXBgAAAADQv+e2y5cvq3bt2ho7dqwaN24sSbp586bCwsK0a9cuubu764033tDAgQPl7u5u5XcCAAAAAM/P7ppxAAAAAAAAAAAAgL2wq3vGAQAAAAAAAAAAAPaEZhwAAAAAAAAAAABgITTjAAAAAAAAAAAAAAuhGQcAAAAAAAAAAABYCM04AAAAAAAAAAAAwEJoxgEAAAAAAAAAAAAWQjMOAAAAAAAAAAAAsBCacQDSVXJysiTJaDRauRLAsaR8pvhswRExrgEAsH1kPcAyyHpwZIxrZCQ04wCkm8jISN27d0+SZDAYJP0vsAF4NkuWLFF4eLgiIiIk/e+zxQEtHMHBgwcVHh5uGteALUlISLB2CQBgM8h6gPmR9eDIyHqwZZbKei4W2SoA/MOGDRv09ddfy93dXYULF1aVKlX06quvysmJcwKAZ3X27FmFh4dr3bp1un//vl566SXVq1dP5cqVk8FgUHJyMp8x2K2ff/5ZW7Zs0Y4dO1ShQgVlz55dXbp0kbe3t1xcOISFdX377bc6fvy4qlWrpoCAAJUtW9baJQGA1ZD1APMj68GRkfVgyyyZ9QxGTqcAkE5u3rypv//+W5MmTdLff/8tSRo3bpwKFCjAzhZ4DteuXdOFCxc0evRoZcqUScHBwRo5cqScnJyUlJQkZ2dna5cIPLMzZ87o6NGj+uKLL5QpUyY1aNBATZo0UZYsWaxdGjKwn3/+WREREdqxY4fOnj2rwoULq3Xr1ipZsqTc3NysXR4ApDuyHmAZZD04MrIebJElsx7NOADpxmg0ymAw6P79+zp9+rQ+++wzhYeHa8iQIapTp47c3d2tXSJgV1LOhkz57+3bt7Vq1SotXbpUWbJk0cKFC9M8DtiD+Pj4xx7gJiUlaejQoTp+/LgKFy6sfv36KWvWrFaoEPif27dv6/z58xoxYoQkqWrVqurSpYu8vLysXBkApC+yHmBeZD04IrIe7Iklsh7NOAAWM3r0aBUtWlQ+Pj6qXr36Y3e4vXv31k8//aQJEyaodu3aphAH4Mn+LXDFxcXpl19+0fjx45UnTx7NmTNHBoOBzxbswjfffKNjx46pSpUqyp07t8qVK5fmcaPRqK+//lo//vijXnrpJfXu3Vve3t5WqhYZzbFjx5QjRw75+fk98lh8fLwmTpyo/fv3q0yZMurXr588PDysUCUApA+yHmAZZD04KrIebFl6ZT2acQAsZs6cOUpKStK3336rokWLKl++fBo4cOAj0yh0795dhw8f1tq1a/XCCy9wIAn8i9Th7NixY4qKipKfn5+Cg4NNn52EhARt3rxZs2bN0uuvv66uXbtauWrgv9m1a5du3Lih7du36/Tp0ypQoIDatWunUqVKpTmjfurUqdq6dau6dOmiunXrst+AxW3YsEHbtm3T4cOHVa1aNQUHBys0NDTNj8/x8fGaPn26fv75Z7399ttq3bo1U0cBcFhkPcD8yHpwZGQ92Kr0zHo04wBY3LVr17Ru3TqtWLFCkjRs2DCVLVvW9KV27949tW7dWrlz59bUqVPZyQJPkPogdNKkSdq8ebOuXLmivn37qnXr1mk+Ow8ePDBNDzR16lR+/IBduX37ti5fvqywsDAlJCSoSpUq+vDDD9OcGdmxY0fdvXtXS5cutWKlyGj27t2rY8eOafr06SpZsqTefvttNWzY0BTEYmNjNXToUJ09e1Zff/010+sAcHhkPcA8yHrIKMh6sFXpkfVoxgEwq+joaEVGRsrd3V158uQxLU9KStLff/+tgQMH6vjx4xo9erRq1qwpZ2dnGY1GrV+/XkuXLtW4ceOUK1cuDiSBfzFz5kx98803+uKLLxQQECAvLy+5uroqIiJCL774omm9v//+Ww0bNlTnzp3VqlUrK1YMPNnZs2d148YNJSQkqFixYmkOaBMTEzVp0iTt3btXpUqVUr9+/ZQpUyZJ0s2bN9W0aVN99NFHaty4sbXKRwaQmJgoFxeXNMsiIiI0fPhwRUZGqmLFiurdu7dpnXv37umNN97Qm2++qQEDBlijZACwCLIeYHlkPTgSsh5sXXpnPe7wCcBshg0bpg8//FD169fXW2+9pWXLlpkec3Z2lr+/v+bOnauXXnpJw4YN09mzZyVJBoNB1apVU0REhH788UfTMgCPun37tg4fPqwxY8aofPnyiouL06JFi9SgQQN16dJFQ4cOlfTwzMrs2bOrU6dOOnnypKSH054AtqR3794aNGiQOnXqpI4dO2rJkiWmx5KSkuTi4qJevXqpVq1a+uOPP7Ro0SIlJibKaDTKx8dHr7zyii5dumTFdwBHtnDhQg0dOlSdOnXSqFGjdO/ePUkPx2ZAQIDGjx+vChUqaM+ePZo5c6bpO9bb21uDBg3S2bNnFR0dLc59BOAIyHqA5ZH14EjIerBl1sp6Lv/3KgDwf2vbtq1iY2MVGhqqTp06KSIiQq+88kqadZKSkuTs7KyZM2cqNDRUQ4YMMe2MfX191aNHDx0+fNga5QN2I1OmTLpz547WrFmjmzdvatasWcqZM6fq1q0rJycnbd68WZcvXzadrfziiy9q5cqVio6OVubMma1cPfA/7du3V3R0tAYMGCAvLy9JMp0JKT38YS85OVmurq7q3Lmzrl27pvXr16thw4bKnj27XF1dVbt2bU2YMEGtW7fWCy+8YK23AgfUvn17RUVFyd/fX76+voqMjFR8fLyk/41NX19fde3aVbGxsdq5c6fKlSunypUrS5KCg4N1+vRpnT9/XiVKlLDmWwGA50bWA9IHWQ+OgqwHW2bNrEczDsBzmzRpkmJjYzVjxgzTJecpl/mmnoLE2dnZtHzAgAEaMmSIli9friZNmkiS3N3d9fvvvysxMVHOzs6cMYkML/UNvFO4ubmpUaNGWrBggXbu3Km2bdvq9ddfV9GiRbVv3z7t2bNHrq6upvXLlCmjihUrKjY2loAGmzF79mw9ePBAM2bMUPbs2Z+4Xsr4d3Nz07Bhw/Taa69p1qxZGjx4sCQpb968Kl68eJobKwPPq1evXrp//76mT58uPz8/Sf/7kTlFytj09vZWjx491KZNGy1ZssQU0AoXLqxatWrpr7/+ohkHwK6R9QDLIOvBUZH1YMusnfVoxgF4LsnJyQoPD9fbb7+dZu7nlLl0U0LWsmXL1KBBA9NOtFChQgoJCdFvv/1mCmi1a9fWSy+99MhcvUBGlDqc7dy5UxcvXtSDBw9UsmRJtWjRQg0bNlR8fLyyZMkiSYqPj9ecOXOUI0cO0wGF9PDAtnv37qaz0QBbcOLECVWsWFHZs2d/4n1j5s+fr9KlS6tUqVJKSEiQh4eHPvnkEy1btkxRUVHy8fFR7ty51atXrzRnWQLP4+jRo/r77781ZMgQ03ep0WhME84k6dy5cwoKClJycrKyZMmiMWPGqH379vr5559VvXp1SVKRIkVUqVKldH8PAGAuZD3AMsh6cGRkPdgqW8h63DMOwDMzGo26fPmyDhw4oOLFi5uW/dOlS5f05ZdfatasWaZ1MmXKpNatW2vPnj26cOGCae7dbNmypd8bAGxYSjibMGGCwsLCtGPHDh08eFDt2rXTV199JS8vL0VHR2vkyJFq3ry53n//fV2/fl3Tpk2TwWBIc88Awhlsyd27d3Xs2DEFBgZKengW2j/Fx8dr8eLFWrBggSSZzgAODg7W2bNn9ddff5nWTfmRAjCH8PBwXbhwQTlz5jQt++cPCF9//bUmTZqk6OhoOTk5KTk5WQUKFFDNmjV19epV03pNmzaVv79/utUOAOZE1gMsh6wHR0XWgy2zhaxHMw7AMzMYDMqePbt8fX31+++/m5b9U+7cuZU9e3b9/fffpnWSk5NVqFAhFShQQImJiY9MzwBAWrNmjdasWaMJEyZozpw5pnsF5M+fXzdu3FDu3LlVuHBhvfjii6pZs6ZWrFghV1dXPlOwSREREZIe3ivA1dVVhw4dkiTTNFcpEhMT5ebmptq1a+vcuXOKjY01hbiCBQvq1Vdf1fnz59O9fmQMd+/eVdasWU1XgDzuh+fSpUtrx44dOnHihKSHP6h5enqqTJky+uGHHxQbG5uuNQOAJZD1AMsi68GRkPVgD2wh6/HtDeCpDRs2THv27JH08IsrW7Zs2rlzp6Kjox+7vpOTk1xdXdPM8+zk5CQ3NzemKgFSSX2GoySdOXNG1apVU9myZbV582aNHDlSYWFhKlq0qIYNG6azZ8+qadOmGjFihDp06CAXFxclJSXxmYLNWbFihXbt2iXp4fd/rVq1tH//ftMyg8FgOhBOGb83b96Uv7+/PDw80kwbUbhwYab+g1mtX7/edAxTtGhRnT59Whs3bpT0+B+efX195eLiooSEhDTLS5curUKFCj021AGAvSDrAZZB1oOjIuvBltla1qMZB+Cp+fn56dSpU5IenvXSs2dP/frrr5o5c2aaL6WUf9+4cUOxsbEqXLjwI4917dpV+fLlS8fqAdtkNBpNZzgeOnRIMTExevDggXx9fbVt2zb1799f/fv317vvvqvbt29r9+7daS6RT/HPua4BW/DgwQOtW7fONM5r1aql2NhYffPNNzpy5IiktAfCd+/e1ZUrV0zTYqXWpEkTBQQEpFvtcGzh4eFavny5vL29JUmBgYEqVKiQli1bppMnT5rWS0pKMh273Lx5U8HBwWmmN5Ee3iPp448/lqenZ/q9AQAwM7IeYH5kPTgysh5slS1mPZpxAJ6ar6+v6SwCSSpbtqw+/PBDzZ8/X8OGDdOZM2ckPdzZ3rhxQ4MHD5azs7MaN25ses7jzj4AMqrk5GTTZ2Ly5Mnq16+f4uPjFRwcrPnz56t79+4aNGiQmjdvLkl64YUXlDdvXu4PALtRvXp1ubm5maYvKVWqlIYPH659+/Zp4sSJWrFihSTp3r17+uuvv9S/f3/dv39fHTp0sGbZyAAKFy4sNzc30xgMDAxU+/bttXfvXs2cOdM0xY6zs7MMBoNiY2M1e/Zs5ciRQ0FBQabtcD8kAI6CrAeYF1kPjo6sB1tli1nPYGQeFQBPKS4uTk2aNFHz5s3VsmVLSdKtW7e0ceNGffrpp8qWLZsCAwNNX2TJycn6/vvv5erqqqSkJM7mAp7gyJEjmj59utq2bauqVatKkoYOHapVq1Zp8uTJKlCggFxdXRUWFqb79+9rwYIF3C8AdiE+Pl4NGjTQyy+/rCFDhpiW79q1SzNnztTJkyeVO3du3b9/X35+fnJ3d9fs2bPZb8CijEajDAaDRo8erXv37mns2LGmx5YtW6ZJkyYpR44cql27tsqXL6/z58/rp59+0s2bN7V06VK5uroqOTmZ72EADoWsB1gGWQ+OiqwHW2SrWY9mHICnYjQalZCQoGHDhikqKkpDhw6Vv7+/6fELFy5ow4YNOnPmjLJmzarChQurUaNGcnZ2VmJiIvObA6mkHBwYjUbt379fHTp0UFJSkmbNmqXq1atLengj5EmTJmnjxo3y8vKSn5+fMmXKpO+++44fgmEXUsbojz/+qKlTp6p379569dVXTY9fv35dly5d0t69e+Xp6anChQvr5ZdfZr+BdPPnn3+qZcuWGjlypN5++23T8j179mjbtm3auHGjEhMTFRQUpMKFC2vIkCFycXFhfAJwOGQ9wHzIesgIyHqwdbaW9WjGAXgmp06dUrNmzdS8eXP1799fkv71QJGzXYD/21dffaVp06bptddeU7du3ZQ3b17TY7t379aDBw+UKVMmVaxYkYNX2J1Lly5p5MiRcnV11QcffKCSJUv+6/r8+ID0kPLD85gxY3Tp0iX16NFDJUqUSPN4dHS07t69q2zZspmmjOK4BoAjI+sB5kfWgyMj68EW2WLWY9QDeGrJycl68cUXFRYWpm+++UZffPGFEhMTTTvSxMTER55DOAMeb86cOWrbtq0kqVOnTvrggw+0Z88eLVq0SFeuXDGtV6VKFdWpU8d0FllSUhLhDHYlMDBQLVu21OnTpzV//nzT/OzSw/1GyjzsKQhnSA8Gg0Fubm6qXbu2IiMjtXjxYp06dcr0eFJSknx8fBQYGGgKZ0ajkeMaAA6LrAeYD1kPGQVZD7bIFrMe3+wAnlrKTvPNN99UdHS0Ro0apRs3bqhp06YqXry4XFxcTFMyAHiyxMRE+fj46PDhw+rWrZumTp2qjz76SElJSVq6dKmcnJzUsmVL5cqV65Hn8qMH7FGNGjUUHx+vqVOnavr06apbt67effdd048NnAEMa6lWrZoiIyM1ffp0xcfHq2nTpipfvrxpPKY+ruH4BoAjI+sB5kHWQ0ZD1oOtsqWsxzSVAB7raQLWzp07FRYWprx58+rFF19Ujx495OLiIjc3NwtXCdiXx03FEBMToy1btmj48OF6+eWXNW3aNEnSF198oeXLl6tGjRrq1q2bsmfPbo2Sgf8s9X0xUvYfT/r3gQMH9MMPP2jjxo2qVq2a6tatq1q1anHFEdLFP49xUv+9du1aLVmyRNHR0WrUqJHatGnDmbsAHA5ZDzA/sh4cGVkP9sLWsx7NOACPSH0QmZCQoLi4OLm5uZkCV+rHU77ULl26pF27dmnFihXy8vKSq6urWrdurZo1a1rrbQA2JfWc0/v371eFChVMj8XExGjz5s0aPny4qlWrpqlTp0qSxo4dqwsXLmjmzJmcfQyblnq/EBkZKaPRqOTkZOXMmTPNeqkPhO/du6cLFy5o9uzZunfvnm7duqXXX39dbdu25Qc+mNWT7kmRejymXufPP//Ur7/+qi+//FIVKlTQCy+8oHfeeUe5cuWSv79/utYOAOZG1gPMj6wHR0bWgy2zt6xHMw5AGqm/oGbPnq2jR4/q8OHDqlixoqpUqaJGjRr963Mk6eTJkzp//rwKFy6soKCgdKsdsEW//fabgoODlTlzZkkPw1n79u31/vvvq2fPnqb17t+/r3Xr1mnYsGFq0qSJRo0aJenxZ6ABtiT12Jw1a5Z27dqlq1evKjExUa1bt1bjxo2VLVu2f32+0WjUwYMHFRwc/K/rAk8r9THKjh07dPHiRUVEROi1117TSy+9lGbdf37PRkZG6vfff9euXbvk5uamzp07c+Y6ALtG1gPMi6wHR0fWgy2zx6xHMw7AY3322WdatmyZevbsKXd3d82dO1fnz5/Xpk2bFBAQ8NjnPOlsBCAjmz59ulasWKHt27frwIEDcnd31+bNm7Vu3To1atRI3bt3N6176dIltWjRQjdu3FC7du3Uv39/peymCWewdZ9//rkWLVqkUaNGKSgoSJMmTdKuXbu0du3aJ/5Yxw8PSC8TJkzQli1blDNnTnl6emrHjh0aPHiwmjZt+tizc/95TBMbGysPD4/0LBkALIasB5gHWQ8ZBVkPtsyesh53TQTwiJMnT2rr1q364osvVK5cOe3fv1+XLl3S+PHjFRERoRs3bqhEiRKPPI9wBjyqYsWK2rRpk8qVK6e4uDgdPXpU2bJlk7Ozs5YtWyaj0agePXpIkry8vFSlShW1aNFCxYoVk0Qwg324efOmfv31V40bN041a9bUtm3bdODAAY0cOVIRERG6cuWKqlat+sjzGN9ID6tXr9aqVas0a9YslSxZUlu3btWOHTsUFBSkqKgoZc+e/ZFA9s8p2mjEAXAUZD3AfMh6yAjIerBl9pb1OJoCoOTk5DR/JyYmKjExUaVLl9bmzZv1wQcfqHfv3nr11Vc1b948bdy40XSpOYB/V65cOZUoUUL37t1TlixZlJSUpNy5c6tJkyZ65513tGTJEg0bNkx79+5Vv379dP36dZUoUULOzs5KSkqydvnAY6Xeb8TExCgpKUnh4eEqUKCAdu/erT59+qhnz55q2LCh9uzZo8mTJ+v+/fuP7G8AS/jnOLtw4YLq1q2rkiVLatOmTerbt69GjBihvHnzql+/frpw4cITf2TmRwQA9o6sB1gOWQ+OiKwHW2bvWY8r44AMzmg0mr6UvvrqKxUrVkyenp66f/++vvnmG82cOVN9+vRRy5YtJUkPHjxQREQEP04B/yL13P8JCQkqXry4ypcvr/nz5+u1117TypUrFRgYqCZNmsjDw0Pz58/Xrl27lDNnTs2fP18Gg0HJycmmm4ADtiT1fmPatGlycnJSgwYNVKJECU2fPl1btmzRwIED1bRpU0kPp3zInDmzMmXKZM2ykUGkHp/79u1TkSJFFBUVpTt37mjLli0aMGCA+vbtq6ZNmyo8PFxHjx7VqVOnlC9fPitXDgDmR9YDzI+sB0dG1oMtc4Ssx5VxQAaWev7mNWvWaObMmTIajSpTpoxKliypTz/9VB07djSFs5iYGEVHR6tgwYLWLBuwacnJyabP1fXr1xUVFaXQ0FA1bNhQgwcPlpeXlxo3bqyoqCgFBgaqXbt2+uGHHzR9+nR99913cnV1VWJiIlMBwWaljO8ff/xRq1atUvXq1ZU7d27lz59fa9asUb169UzhLD4+XmfPnlX+/PmtWDEyitTHNdOmTdOoUaN069YtBQcHa9++ferXr5969eqlFi1aSJLc3d2VNWtWZc2a1ZplA4BFkPUA8yPrwdGR9WCrHCXrGYzMPQBkePPnz9eff/6p4sWLq23btpKk33//XZ9++qnOnTunTp06KTk5Wbt371ZkZKRWrVolFxcurAX+KfU81NOnT9fmzZt19epVtWjRQp06dVKmTJl06NAhDR8+XA8ePNCsWbO0f/9+vfrqq/L3939kG4Ct2rRpk+bNm6dChQpp5MiRpuVdunTRH3/8oZIlSyp37tw6duyYoqOjtXr1arm4uHATb6SLnTt3avbs2WrXrp1q1aolSerQoYMOHTqkIUOGqGLFikpMTNTo0aN1//59fffdd3zvAnBYZD3APMh6yCjIerBl9p71aMYBGVDKAWDKjrJ79+7atGmTypcvrylTpihbtmxKSkrSxYsX9dVXX2nfvn3Knj278ufPr9GjR8vV1VVJSUlMqwA8wcSJE7Vs2TJ17NhRBoNBn332mTp37qz27dvLy8tLhw4d0ujRo3X8+HEFBwdr7dq1fJ5g0/75w8GsWbO0ZMkSxcTEaMOGDWnONpsxY4aOHTumxMREFShQQL1795aLi4sSExP5cQ8WkTr4Hzx4UGPGjNHFixc1d+5clSxZUtLDMdyhQwedP39e169fV6FCheTm5qYFCxZwXAPAoZD1AMsi68HRkPVgyxwt69GMAzKwvXv3qnLlypKkUaNG6fvvv9egQYPUqFEjZc6c2bTezZs35ePjIxcXFxkMBnaywL/Yu3evhg4dqsmTJ6t48eI6ePCgWrVqJUl677331KtXL3l6eioqKkq///67Xn75ZTk7O3OWJOzC1q1bValSJXl7e2v58uWaMWOGgoODNWrUKNMZv9L/bqqcMqbZbyA9GI1GJSYmat68eZo9e7aKFi2qadOmpTmmOXz4sCIiIuTn56fSpUvL2dmZ8QnAIZH1APMj68GRkfVgyxwl69GMAzKogwcPql27dmrevLk++eQTSdLAgQO1bt06DR48WPXr15e3t7ektGfJcNk58O+WL1+uFStWaNGiRTp58qQmTpyoN998U25uburVq5c+/PBD1ahRQ6VKlTI9x5bO0gGe5PLly3r11Vf12muvacyYMfL29taCBQu0fPly5cmTR4MHD5a/vz/jGVbx1Vdf6fTp0xozZoycnJw0f/58LV++XCVKlNDQoUNNxzT/xHgF4IjIeoBlkPXgqMh6sGWOlPU4LQPIoAIDA/X+++9r69atGjdunCRp7Nixql+/vsaMGaMff/xR9+7dk6Q0Z3ARzoD/STmfJfV5LS4uLnJyctKtW7e0fv16FSxYUJUqVVJISIicnZ01Y8YM/fjjj2m2Y2sHB8Dj5MmTR7Nnz9aePXs0ZMgQ3bt3Ty1btlSTJk105coVjR49WhEREYxnWEWOHDn0ww8/aOzYsUpOTlabNm3UqFEjnThxQqNGjTId0yQlJaV5HuMVgCMi6wHPj6yHjISsB1vmSFmPZhyQATzuAlh/f3+1bNlSjRo10vr1600hbdy4capXr56GDBmiffv2pXepgN1ITk42/WCRkJCg+Ph4xcfHq2HDhhoxYoSMRqN27dqlSpUqKSAgQElJSXrjjTf05Zdfqm/fvlauHvh3T5o4oWrVqvr888+1Y8eONCHtnXfe0e+//66FCxemc6XIiFKmxkmtUaNG+uyzz7RkyRKNHj1aRqNR77//vt566y2dPHlSffr0UUxMjE0GMgB4HmQ9wPzIenBkZD3YMkfPerYzYSYAs0uZZiQ5OVnOzs5atmyZ4uLiTHOa+/n5qXnz5kpOTtbSpUvl7u6unj17auzYscqbN69q1Khh5XcA2KbU0/l89913OnLkiC5evKisWbOqf//+Cg4O1v79+/XXX38pV65cMhqNmjBhgpKSklS9enUZDAabvFweSLlvjKurq6SH00HcvXs3zY8KVapU0eeff65u3bpp5MiR+uSTT9SyZUvlyJFDtWvXtlbpyABSjmtSvn+PHTumYsWKmR6vV6+ejEaj+vXrJ0kaNGiQ3n//fd2/f18RERFyd3e3St0AYAlkPcAyyHpwVGQ92LKMkvW4Mg5wUBcvXtRnn32mxMREOTs76+bNm9q0aZMWLlyoFStWmNbz8/PTe++9p6JFi+rLL7/UkCFDJEldunSRi4uLEhMTrfUWAJuUOpxNnDhRM2fOVMmSJRUaGqo///xTXbp00a1bt5QnTx4VKlRILVq00Jtvvqlr165pxowZMhgMMhqNhDPYnFu3bmnBggU6f/68JOnq1atydXXVnDlzNGvWLNN6RqNR1atXV4cOHbRmzRoNGDBAMTExeu211+Ts7PzI1BCAOVy8eFHnzp0z/X3kyBG98847WrBgQZr16tevr9GjR2vp0qWaPn26kpKS1K1bN40bN05OTk6PPdMSAOwNWQ+wDLIeHBVZD7YsI2U9rowDHJTBYNDmzZt1+vRp+fv7q2rVqurRo4fmzZun+fPnKzk5We+++64kKVu2bCpcuLCSk5MVHx+f5gDUxYWvCUCSdu7cqRo1apg+G8ePH9f27ds1depUlStXTjt27FBCQoK6d++uixcvqmDBggoLC9Off/6p2NhYtWrVyvSjB58r2CJPT09t3LhRW7ZsUfHixZUpUyZ1795dBoNB48ePV1JSkj766CPTlD0+Pj6qW7euoqOj05yFxo8PsIR169bp559/Nt3LIleuXPrggw80duxYOTk5KTQ01LRu+fLllSVLFn355Zfy8fFR+/btJT38cSH1vZEAwF6R9QDzIuvB0ZH1YMsyUtZjDwE4qICAAHXv3l1hYWG6e/euGjVqpOLFi6tdu3aaM2eOvvvuOzk7O6tx48aKj4/XlStXVK9ePVNoSx3SgIwuNDRUOXLkUNWqVU0Hn3fu3FFMTIzKlSunbdu2qU+fPurXr59ee+019ejRQ/ny5VO/fv1UvHhx03aSkpIIZ7BZnp6eWrt2rV5++WWdPn1an3/+uTJnzqwWLVrIaDTq008/lYuLi1q0aCE3Nzf9+uuvql+/vurXry+J/QYsq169elq8eLHq1q0rSVqxYoU++ugjSVJYWJiSk5PVsmVLSQ/HcoMGDVSrVi2VLl3atI2UHxcAwN6R9QDzIeshIyDrwZZlpKzHXgJwQEajUa6urjIYDHJ2dlbu3Lk1Y8YMTZkyRcWLF1f79u319ddfa8qUKVq3bp3u3bunmJgYTZo0yfR8drLAQy1atFBsbKzGjx+f5iwwNzc3ZcuWTbNnz9b06dM1YMAANWvWTPHx8bp586ayZ8/+yLY4iwy2LDk5WWfOnJEk5cmTR9OnT1e+fPlUpEgRtWrVyhTSVqxYIYPBIFdXV73++uum57PfgCXlz59fFStW1A8//KAXX3xRBoNBbm5u6tKliwwGg0aPHq0bN26oWLFiWrZsme7fv6/+/ftLEmepA3AoZD3AfMh6yCjIerBlGSnrGYxGo9HaRQAwj3+eqRIREaH4+Hj9/vvvmjlzpnLmzKlp06bJ09NT4eHh2rlzp44cOSI/Pz8NGTJELi4u3GgYSCU0NFRxcXFasGCBPD09lZCQYLrZcXR0tN555x1dvHhRPXr0UOfOnSVJ8fHxatu2rWrWrKlOnTpZs3zg//S4MxwTEhIUFxen5s2bS3p4v4wiRYpIkvbu3asdO3bohRdeUIcOHdhvwKJSbuKdYvny5cqSJYvGjBkjPz8/jR8/Xvny5dODBw/07bffaurUqcqZM6f8/f31zTffyNXV9ZFtAIC9IusB5kXWg6Mj68GWZdSsRzMOcBCpd7I7d+7UjRs3lD9/fpUrV06xsbFat26d5s6dq1y5cmnGjBlyc3PTgwcP5OXlZdqGvZ1NAFhSynQNX3/9tby9vdOEszNnzqhgwYI6c+aM2rZtqzx58ujVV19V9uzZtXr1at28eVOrVq3i8wSblnq/sXbtWh0/flwFCxZUxYoVFRgYqOvXr6t9+/YyGAyaOHGi8ufPrzt37sjf39+0DfYbsJTU4/PixYvKnDmzvLy85O7urjNnzqhjx47y9/fXhAkTFBgYKEm6fv267t27p6CgIDk5OTE+ATgMsh5gXmQ9ODqyHmxZRs56NOMAB5D6TIBPP/1Uy5cvl7e3t65evarhw4erefPmio+P1w8//KDZs2fL29tb7u7ueuONN9SqVatHtgFkdOPHj9e8efO0cuVKhYSEKC4uznTT4g8//FAPHjzQrFmz5OHhofPnz2vIkCG6evWqfH19lTdvXk2YMEGurq6cRQablfo7f/z48VqxYoUCAwN1+vRpNWzYUK1bt1bBggV1/fp1vf/++7p3756yZMmi0qVLa/jw4dYtHg4vdTibNm2aNm3apDt37qhp06Zq2LChAgMDdfbsWXXs2FF+fn7q3bu3Dh06pNdee00FChR4ZBsAYM/IeoB5kfXg6Mh6sGUZPevRjAMcyMyZM/Xtt9/qiy++UOHChfXJJ59o8+bNaULaxo0btWHDBt27d0/z5s0znf0F4H8WLVqkNWvWyNfXV7169VLhwoUlSd26ddO5c+c0c+ZM5cmTx3QAEB8fr3v37slgMChLliwyGAx2e5YOMpb58+dr9uzZmjp1qsqUKaNRo0ZpxYoVevvtt9W6dWsFBwcrKipKn376qRISEjR69GjGNdLNhAkTtGTJEvXq1UtXr17VihUr1LBhQ7Vo0UKBgYE6d+6c2rdvr1u3bqlgwYJasmQJP4oBcFhkPcA8yHrIKMh6sGUZNevRjAPsWMrZLkajUXfu3FH37t3VqlUrvfbaazp8+LD69++vF198Udu3b9fw4cPVrFmzR57LQSTwP6nPIFu1apUWL14sX19fjRw5UhMmTFB4eLgpnD3uOf+2DLAFqc8gS0pKUteuXVW+fHm9//77+v333/XJJ5+oePHi2rp1q9544w21adNGhQoVSrMN9htID7/88ovCwsI0depUFS1aVMeOHdM777yj7Nmzq379+mrdurVy586te/fuaf/+/apRo4acnZ3t+ixJAEiNrAeYF1kPjo6sB3uRkbOefVcPZGCpDwBv3LghJycnHT58WJkzZ1ZkZKQWL16sJk2aaOLEiapUqZLCwsIUFhamS5cuSZIp2LGTBf7HYDAoOTlZktSoUSM1a9ZMd+/eVaNGjfTbb79p0aJFacJZynMetx3A1hiNRtOB66lTp3T//n2dOXNGPj4+ioyM1LJly/TGG29o3LhxatSokVavXq3+/ftr9+7dabbBfgOWkPLdm+Lvv/9WtmzZVLBgQZ04cUKTJ0/WpEmT1KFDB33zzTf67rvvtG/fPnl7e6tWrVpydnZWUlKS3YczAJDIeoAlkPXgyMh6sGVkvf+x/3cAZEDJyclp5n8eOHCgYmJi1KtXL/n6+mrnzp1KTk5W1apV5enpKV9fXxUpUkTnz59X7ty5TdvhIBL4n6SkJEmSk5OT6UChcePGCg0NVUBAgAICAnT79m1Jjx5IALYu9X5j3Lhx6tGjh3x8fNSlSxe9+OKLOnTokP7++29VqlRJkuTh4aHChQurZs2apmUS+w1YRuofD+bOnavffvtNMTExypIli6Kjo7Vx40bTDeffffddZcqUSZs2bdLatWtNz5fkENOWAABZDzA/sh4cGVkPtoyslxbNOMAOpXyJ/frrrzp58qT69OmjgIAAvfvuuypcuLCWLFmiHDlyqFixYoqJiVF0dLR69eqlefPmpTn4BCAtX75cycnJpjNtpLQhrWHDhmrVqpUSEhI0fPhw/fXXX3yOYHdS9htHjx7VmTNnNGzYMEkPzwouWbKkNm7cKD8/P5UrV06SdPr0aTVq1Egff/xxms8GYG6pr/5Yvny5Pv/8c8XFxSk0NFR9+/ZVYmKitm/frjJlyih79uy6fPmySpcurV69emnkyJGS+OEAgGMh6wHmQ9ZDRkDWg60i6z2KZhxgp3bs2KHOnTvrzp07ypEjhyQpc+bMMhgM8vPz0+XLl7Vjxw716NFDUVFRprNdUp+RAGR0a9as0aRJkzR27FgZjcYnhrTGjRurWbNmun//vsaOHavTp0/zOYLd2bFjh95991399ttvypw5s6T/Hdj6+Pho27ZtWrhwoVq1aqWrV6+qefPmpmmuHOUsNNielDH43Xff6dChQxo4cKAqVqwoSQoODtaJEyd05coVVahQQffv39eUKVPk4eGhN998kx/LADgssh7w/Mh6yEjIerBFZL1HsXcB7FSWLFlUvXp1nT59WqdPn5Yk0/y55cqV0/nz5zVy5EjFxsZq4cKFcnFxUVJSksOdUQA8j+rVq6tJkyb69ddfNWrUqH89a7Jx48Zq3ry5zp8/r+XLl1uzbOA/SZnOIeW/NWvW1Hvvvad79+5p27Ztunv3rmnd0NBQhYSEaPny5cqSJYtWrFjBfgPp6qefftKqVau0fft2RUdHm5aXKFFC/v7+euWVV9SsWTNduXJFkydPNt33hR/LADgish7w/Mh6cGRkPdgTst7/GIwpn1oANutJX0AXLlxQWFiYjhw5ooULF6po0aKmx65evarExETlyZNHTk5OSkxM5EasQCrx8fFyc3NTUlKSPvvsM+3atUvVqlVTnz59ZDAYlJSUZDpDLPVncOfOnapatSpnj8Gm/XO/ERcXJ3d3d0nS8OHDtXTpUg0ePFhvv/22vL29JT0Mcrdv39YLL7wgg8HAfgMWk3q6ktT69++v9evXa9iwYXrzzTfl6emppKQkXbhwQbt27ZK7u7uaNGkiFxcXxicAh0HWA8yPrAdHRtaDLSPr/TuacYCNS72TXbdunS5cuKArV66oTJkyaty4sa5fv67Bgwfr8OHDWrRokYoUKfLIjtlRzyYAnlXqg4MlS5Zo//79+umnn5SUlKTmzZurf//+cnJyemJIk5TmMcCWpB6rS5cu1eHDh3X58mUFBgaqb9++ypo1q4YOHaqVK1dq8ODBevPNN00hLcWTDqCB55V6fJ46dUqxsbG6c+eOqlevLknq0aOHdu3apeHDh6t27dry8vJ6ZBt8/wJwFGQ9wPzIenBkZD3YMrLe/41mHGAnJkyYoDVr1uiVV17RnTt39PPPP6tmzZr6/PPPdfbsWY0ePVpHjx7VvHnzVLx4cWuXC9iFWbNmafbs2QoLC1OmTJm0adMmnTx5UqVLl9aQIUMc+tJ4OL4JEyZo7dq1aty4sQICAhQWFqaKFStqxowZypQpk4YOHaq1a9eqe/fuat68uTw9Pa1dMhxc6uA/ZcoU7dy5U3fu3FFCQoKCgoI0ZswYBQYGqmvXrvr11181fPhw1apV67EhDQAcCVkPMD+yHhwZWQ+2hqz337DHAezA1q1btX79es2YMUMjR47U22+/LScnJ9WtW1fnz59XcHCwhgwZosDAQE2aNMna5QI2z2g0KioqSnv37lWfPn1Uv3591axZU5988onefPNN7du3T59++qmMRqPD3jQWju3IkSPatGmTJk+erJ49eyp37tzy9PRUixYtdPbsWUnSiBEjVL16dW3fvl0eHh5WrhgZQUo4++qrr7Ro0SINGjRI69evV4sWLXTgwAHdunVLkjRt2jRVqlRJffr00ZEjR6xZMgBYHFkPMC+yHhwdWQ+2iKz339CMA+zA1atXFRwcrJIlS2rjxo3q37+/+vXrp1KlSunTTz/Vvn37FBQUpMmTJ2vOnDnWLheweQaDQR4eHrp586auXbtmWu7t7a3WrVsrICDAdPCQEtIAexIZGSkvLy+VK1dOW7duVffu3dWvXz/VqlVLkydP1owZMyRJU6dO1TfffCODwSAmS0B6iI+P19GjRzVw4ECVL19ee/bs0dy5czVmzBglJCRo2rRpkh6GtA8++EAVK1a0csUAYFlkPcC8yHpwdGQ92Cqy3v+NPQ5gwxITEyVJN2/eVKZMmbRz504NHDhQffv2VWhoqJydnbV371799ddfkqR8+fJxZhfwGI/7TKTc9P6PP/7Q1atXTQenrq6uKl68uPLly6fMmTNz0Aqb97gxmilTJrm5uWnevHnq27ev+vfvr9DQUMXGxur27duKjY01rZuy3+C+AUgP8fHx+uOPP+Tu7q69e/eqb9++6tWrlxo3bqyLFy9q0aJFOnfunCSpZ8+epht4A4CjIesB5kHWgyMj68GekPX+by7WLgDA//xzvvKUG1bWrFlTX3/9tTZv3qyJEyfqzTfflPRwp5wvXz7lzJkzzXY4swv4n9SfqxMnTujevXsyGAwqU6aMBgwYoEaNGmnSpEn68MMPFRQUpLi4OIWHh+v1119Xly5duJcAbFrqsRkfHy9JcnNzU1BQkP7++2+NHz/edJ+AlMecnZ3l5+eXZjuMb1jC4747PTw8VLZsWS1YsEAnTpzQgAED1KxZM0kPb9adLVs2+fv7p3mOiwuRBYD9I+sB5kfWgyMj68GWkfWeTcZ6t4ANSz09wuLFixUeHq7Lly/rrbfeUsWKFdW/f39NmjRJ58+f1/Hjx2U0GvX555/L2dlZ1apVs3L1gG1K/bmaMmWKfvzxR0nSnTt3lD9/fvXr108zZ85U165dFR4eLmdnZ3l4eCg6OlrTpk0jnMGmpR7fs2fP1u+//66zZ8+qZs2aatasmaZOnaqmTZvqxIkTWrJkifz8/PTtt98qMTHRFNgAS0n93fnnn3/q5s2b8vf3V4ECBfTOO++offv2qlSpkqpXry5Jio6O1pYtWxQUFMQN5gE4HLIeYH5kPTgysh5sGVnv2RmMXJMNWF3qL7EJEyZoxYoVqly5sqKjo7Vnzx698847ev311/XXX39pypQpcnJyUvbs2ZUjRw7NnTtXrq6uSkpKMp1dCSCtefPm6euvv9aUKVNUoUIFff7555o7d67mzJmjcuXKKSIiQlu2bNHff/8tf39/NW3aVC4uLnyuYLNS7zdmzJihb775Rq1bt9aVK1d08uRJ3bt3T1OnTtW9e/c0adIkhYeHK3/+/PLz89MXX3zBfgPpZsKECVq3bp3i4uJkNBoVEhKiUaNG6dixY+rXr5/y5csnb29vxcfHKzY2VitXrpSrqys/jgFwGGQ9wLLIenA0ZD3YC7Le06MZB9iQCxcuaPr06WrevLnKlCkjSfrhhx80YsQINWnSRP3799fFixd17do1+fj4qHDhwnJyclJiYmKGu6wXeJLr16/Lz89PBoNBiYmJcnZ2Vvfu3VWiRAl17NhRmzdv1sCBAzVw4EDly5dP+/btU9euXR/ZDgevsAeXLl3SlClTVLduXb366quSpAMHDmj+/Pm6du2a5syZI2dnZ0VHR8vV1VU5cuQwfTbYb8ASjEaj6Z4UP/30k0aMGKGxY8eqYMGC2r17t1asWKFbt25p/vz5unjxovbs2aMbN24oODhYLVq0MN03gPEJwNGQ9YDnR9ZDRkLWg60h6z2/jNmCBGzQ5s2b1bBhQ/3yyy/KlCmTaflbb72lfv366dtvv9WJEyeUN29eVaxYUUWLFjXdiDUjf4kBqUVHR2vt2rU6ffq06W+DwaDw8HAVLlxYv/32m/r376++ffuqSZMmioiI0FdffaULFy48si3CGWzdli1bVKdOHf38889ydXU1LS9fvrxCQ0P1999/648//pCPj49y585t+uGC/QYsKSWcLV26VL/99ptq1qypSpUqKXv27GrQoIE6duwod3d3ff311ypTpoy6du2qsLAwtW7d2nSWOuMTgKMh6wHPj6yHjISsB1tE1nt+NOMAK0m5KDXlv9myZVO1atUUFRWluLg4STL999VXX9ULL7ygy5cvP7KdjHpZL/A4cXFxmjZtmsaNG6fBgwfriy++kCS99NJLGjRokFq3bq1hw4aZ5lB3cXFRgQIFlDlzZmuWDfwnycnJaf6uU6eOmjZtqujoaJ06dcp0U29Jqlq1qjw9PXXy5MlHtsN+A+lhxYoV+vLLL3Xu3DklJiaallerVk0VKlTQ1q1bFRsb+8jz+HEMgCMg6wHmR9aDIyPrwZ6Q9Z4dn1DACpKTk01nE9y5c0eSVLZsWXXr1k2lS5dW9+7ddenSJbm7u0uSEhIS5OPjw0Ek8H/Inj27fv75Zx06dEgrV65U+fLlJT086zhbtmzKly+fXnnlFUnSgwcPtGrVKgUEBOiFF16wZtnA/yn1nOrXrl3TpUuXJEkjRozQm2++qVmzZmnv3r2mA+G7d+8qU6ZMCgwMtFrNyDj++eOBJC1ZskSvvfaafvvtN/36669pQlrhwoWVK1cu07EQADgSsh5gGWQ9OCqyHmwZWc+8uGccYEWzZs3Sxo0b5e/vrwYNGqhevXo6e/asxowZo9OnT6tPnz4yGo1au3at7ty5o6VLl3IWAfAv4uPjdezYMYWGhsrT01OlS5fWwIEDVahQIS1ZskQLFy7UtWvXFBQUpJiYGBkMBi1fvjzD30AW9mPy5Mn64Ycf5OTkpBo1amjIkCGSpB49emjnzp1q0KCB8uTJowMHDujq1atatWpVhp8GApaV+r4B69at0927d+Xj46O33npLktS2bVudO3dOw4cPV0hIiNzd3dW9e3e98MILmjJlihUrBwDLIusB5kXWg6Mj68HWkPXMj2YcYCULFizQ1KlT1bx5c+3cuVNOTk5q0qSJWrRoobNnz2rEiBHat2+fXn75ZVWpUkUtWrSQp6cnNxoG/uFJwerq1at66623FBISorCwMBUoUECnTp3S9u3bFR0drVy5cqlZs2bcQBY2LfXB7+rVqzVx4kR16dJFFy5c0LJly/T6669r3LhxkqQBAwZo9erVeumll1ShQgX16tVLkhjfSBcTJ07Ud999Jz8/P127dk1t2rRR3759JUnt2rXT3r175efnp6JFi+ru3bv69ttv5ebmlmaMA4CjIOsB5kHWgyMj68FekPXMh08rkE5SH0QmJyfrxo0bGjZsmOrVq6c2bdpo6NChWrZsmQwGg0JDQzV48GBNnDhRBw4c0ODBg+Xp6anY2Fh5eHhY+Z0AtiP152rDhg06e/as8ufPr3LlyilXrlxavHixQkNDFRYWpiFDhqhQoULKlSuXvL29TdvgBrKwVanHd0JCgtzc3PTxxx+rWbNmunfvnoKDgzVq1ChJ0rhx4zRu3DgZDAZt3LhRTZo0MW2H8Q1LSD0+7969q99//10LFixQ5syZ9dNPP2n8+PFKTk5W//79NW/ePPXo0UMbN25U+/bt9e6778rNzU0JCQlpbkgPAPaKrAeYH1kPjoysB1tG1rMcPrFAOjAajaYvsYULFyoyMlLr169XgQIFJElZs2bVkCFDNHLkSFNIa968ufr06aMRI0aoVatW+vbbb1WwYEFrvg3ApqT+XI0fP16rV6+Wj4+P4uPjVaNGDXXq1EmFChXSokWL1KxZM/Xr10+JiYkqW7ashg0bZjpDh7OPYYtSj++5c+fqwIED+uWXX0w3pPf29la9evUkSWPGjJHBYNDYsWM1duxYJSUlaezYsYqLi1OjRo3k5eVltfcBx5Q6nB05ckTXrl0z3bfC19dXDRo0UGJioiZNmiRJ6t+/v6ZMmaL27dtrxowZypUrl15++WVlypTJmm8DAMyCrAeYH1kPjoysB1tG1rMsJkwGLCz1DbwnTpyoCRMm6JdfflFkZKRWrlxpWs/f319DhgxRnjx5NGPGDG3dulWFChXSoEGD5O/vrw8++EAJCQliZlngoZTP1dy5c/XDDz9o2rRp2rRpk8qVK6cff/xRX331lS5fvqxChQpp2bJlCgwMVOHChTVo0KA0zwdsTeqpHL766it9/vnnyp49u3x9fbVr1y4dOHBASUlJypw5s+rVq6fBgwdr1apVmj59uiTp008/VaVKlTRr1iwlJSVZ863AQaX+ceyjjz7SsGHD9PPPP+vUqVOSpBdeeEHvvPOO+vTpo++++850v4s5c+aoTJky+vjjj7V3716r1Q8A5kLWAyyDrAdHRdaDrSPrWRb3jAPSyd27dzVo0CB9/PHHypMnj3799VcNGTJERYsW1dy5c03rRUREaOHChfr4449Nl/OGh4fL29tbuXPntlb5gE1YsWKF3nnnHUkPf/yIiYlR165dVa9ePb377rs6duyYevfurUKFCunkyZOqVq2aOnTooFy5cqWZ+od51WEPwsPDNXv2bL377ruqUKGC7t27pwYNGsjb21tDhgxRmTJl5OTkpKioKB04cEA1atRIM66vX78uf39/K74DOJrUPx7s2LFDn376qfr06SMXFxcNGjRIgYGBGjRokEqUKCFJun37tr777jv9+uuvmj9/vtzc3CRJ3bt3V/fu3U1XjQCAvSPrAc+PrIeMhKwHW0PWSx8044B0sHDhQs2aNUt+fn6aMmWK8uTJo7i4OO3YsUPDhw9XSEiI5syZ88jzmF8X+J+9e/eqXbt2atOmjQYOHChJunPnjlq2bKmOHTuqQoUK+uKLL1SgQAF17NhR3bp1086dOxUYGKjPP/9cwcHBksQNZGEXNm3apDlz5ujGjRuaOXOmihQpIunhj32NGzdW5syZNXjwYFNIS5GYmMiUPLC4Xbt26aeffpKvr6+6d+8uSbp06ZLeffddFShQQIMGDVLx4sUlSdHR0fL29pbBYFB8fLwppAGAoyDrAc+PrIeMhKwHW0bWsyymqQTSwSuvvKKcOXPq+PHjunr1qpKTk+Xu7q6aNWtqxIgRCg8PV8OGDR95HuEM+J+yZctq9OjRWrRokcaOHStJypIlixo0aKBChQrp0KFDun//vsqWLStJCggIULFixfTKK68of/78pu0QzmAPypYtq8DAQN24cUPr169XcnKyJMnX11crV67UgwcP1KNHD9NUESlcXFwIZ7CoqKgozZw5U0uWLNGJEydMywMDA7Vs2TKdO3dO48eP15EjRyRJmTNnlsFgkNFoJJwBcEhkPeD5kfWQkZD1YKvIepZHMw4ws5SdaGo5c+bU1KlTFRwcrLCwMJ06dUpGo1Hu7u6qXr26+vfvL39//8c+F8BDbm5uevvttzVs2DAtWLBAo0aNkiR16tRJxYoV048//qhs2bKpTJkykqSLFy/q9ddfV+/eveXs7Mx86rBZ//zuj4uLU/bs2TV8+HDVr19fP/30k+bNm5cmpC1ZskRlypRRoUKFrFEyMpB/jk8fHx9NmDBBtWvX1smTJ/X999+bHgsMDNTSpUt14MABrVmzJs3z+HEMgCMg6wGWQdaDoyLrwZaR9dIf01QCZpT6ktzNmzfr9OnTun37tooXL66GDRvq+vXr6tChg6SHN/h+8cUXH7mUNzk5Oc1l6EBG98+pRuLj47VmzRqFhYUpNDRUn3zyiSSpc+fOioyM1HvvvaeVK1cqOjpaK/4fe/cdX/P5/3/8cTJlWDEbYqtRqyilLTXa2rNqrxpFbRKC2DuIGSOo2KP2JopQOmjV3ru1QwaRdc7vD7+cJuj4fJvIycnz/k9Jzjm369T1fl/X8/2+3tdr/XpsbW21XYlYpJf75dq1azlz5gynT5+mRo0a1KtXj6xZs+Lj48Ply5dp2LAhHTp0eGWMiIuL0wpJSRYJ+9a1a9eIiorC1taWwoULExISwrBhw7h37x6ff/45LVu2NL/v/v37ZMmSRf1SRKyKsp5I0lPWE2ulrCeWTlkvZWgWKJIEJk6cyLNnz8why9fXlwkTJnDhwgUiIiIYPHgw06ZNI0eOHCxcuBCTycSgQYM4c+YMQKJHeRXORP5kNBrNE9jo6GiioqIAaNasGcOHD2fVqlXmVZN9+/YlKiqKpUuXki5dOtatW2deJalwJpZm5MiRXL582fx3X19f/P39cXR0pFatWsycOZNx48bh4ODA8OHDKVSoENu2bWPOnDm8vI5Kk2BJardu3UoUzmbPnk3v3r3p3r07zZo1o0+fPoSHhzN8+HCyZcvG+vXrWbNmjfn92bNnx9bWltjY2JT6CiIiSUZZTyR5KOuJtVLWE0umrJeyNBMU+Y9atWrFkSNHsLOzA16sktyyZQvTpk1j5syZfPzxx9ja2lKqVClu3bpFjhw5WLRoEffu3WPp0qUp3HoRy5Vw5fCSJUsYPHgwTZo0oX///hw7dowvvviCkSNHsnr1aiZOnEjRokXZtGkT8+bNY8GCBdjb2xMbG6vJq1ic+HEjT548APzwww9s27aNmTNnMmTIECpXroytrS2tWrXi0qVLZMiQgWHDhpE5c2b++OOPFG69WLv69esTGBhoPnfOnz+fFStWMHjwYPbv38/nn3/OwYMHCQ0NJWfOnIwaNYrs2bMzf/58goKCEn1W/NxIRCS1UtYTSR7KemKtlPXEkinrpTzdjBP5D1q3bk1UVBRr1641r3i8fv067777Lu+++y579uzB29ubESNGULJkSYYNG8aRI0fIkSMH27dvNxcmFpFXxYezqVOnMn/+fMqXL0+HDh24dOkSnTt3JjQ0lM8//5wRI0awcuVKBg8ejL29PTly5MBgMGA0GjU5EIvTrl07jEYjW7ZswdHREYDQ0FA8PDwoVaoUO3bsoE2bNgwZMoSKFSvi4+PDli1byJw5MzNmzGDcuHHmAskiSa1ly5bY29vTt29f4MUq9WPHjtG/f38++OAD9u7dy6ZNmxg+fDhPnz5l1apV5MiRg0GDBlG7dm2qVauWsl9ARCQJKeuJJB9lPbFGynpiyZT1LINuxon8H/Xq1YtTp07h7+9PunTpzINlbGws9vb2bN++nUGDBuHl5cUXX3xBREQE58+f5+HDhwC4ubmp0LDIPzh79izfffcds2fPplWrVuTMmZOQkBDGjh3L5cuXuXXrFs2aNcPT05Pff/89UfFZbQMklqZ79+789NNPdO/enXTp0pl/HhUVxR9//MGGDRvw8fHB09OT1q1b4+joSGRkJNevXwfA1dUVGxubRFv6iCSVr776iocPH7JhwwZcXV2JjY0lIiKCs2fPUqRIEY4fP46XlxcDBgygSZMmXLlyhRkzZnDv3j3y5s2Lp6en5jUiYjWU9USSn7KeWBNlPbFkynqWQ6OXyP9By5Yt+eWXXzAajQQGBhIaGmoeLD08PNi1axeDBg1i4MCB5iKX6dOnJ3v27GTMmDHRZ2lbBZE/JQxY8GLiGhkZybvvvktQUBC9e/emb9++fPrppyxfvpxVq1YB0Lx5c5YuXWqevIpYmpYtW3L27FmKFy/OqlWrOHLkiPl377zzDpkyZcLHx4dOnTrRqlUrAJ4+fYqNjQ0eHh6JPksXHySpdejQgYMHD1KoUCHOnz8PvNh2xM3NjXLlyjFixAg6deqEj49PouLdHh4eZMqUKdFnaV4jIqmdsp5I8lDWE2ulrCeWTFnPsugIF/kftWjRgqioKA4dOsTkyZNZsmQJc+bMISwsDHix/267du3MhSxPnjzJpUuX8Pb2xsnJiQ8//DAlmy9isUwmU6K6AT/88APPnz8nXbp0LF261Lz6uHXr1jg4OPDgwQMeP34MgIODg3k7B01exdI0atSIqKgoDh48iKenJw8ePGDx4sUcPXoUgIIFC1K3bl08PDw4efIkhw8fZt++ffTr1w97e3saNmyYwt9ArFnLli15/vw548eP5969e8yaNYvffvvN/PuKFSvy6NEjypQpQ7169YAXW5ocPHiQ3Llzm7duExGxBsp6IslDWU+slbKeWDJlPcujDZZF/gcrV67EwcGBxYsXY2NjQ506dYiJicHb2xuAHj16kClTJgYNGkRUVBSzZs3i2bNn5MuXD1dXV1asWGF+rFerCUT+ZDKZzCuOV69ezaxZs1i8eDGlS5fGxcWFiRMnJlp9HBkZiclkIn/+/Ik+R9s5iKX55ZdfKFasGEOHDgWgUqVK9OrVy9zHjUYjH3zwAZ06dcLOzo6goCA6d+5MkSJFyJEjB2vWrNG4Iclm0KBBPH78mM2bN+Po6IidnR2LFy8mICCAzp07U6ZMGVq3bs0ff/zBd999R926dSlYsCD3798nJiaGDRs2mC+O6fwrIqmdsp5I8lDWE2ulrCeWTFnPMhlMqgop8j+JiYnB3t4+0clo8+bNeHt706ZNG77++mvz9iQnT57k6dOnuLi4UKJECWxsbIiNjVWhYZEEEh5LW7ZsYf/+/VSoUMEcxs6fP4+npydGo5FmzZqRLl069uzZw4MHD9i4caOOJ7FoMTEx2NraYmNjkyhkHTx4kJkzZ+Lm5kb79u3NK+mjoqK4efMmmTNnJkuWLBgMBo0bkiziC3aXK1fOXGAeYNu2bSxcuJDcuXPz5ZdfUrZsWQCCgoL46aefiIyMxMPDgy+//BI7Ozv1TxGxKsp6IklLWU+smbKeWCplPculm3Ei/5LRaPzbLREShrT4VZP/62eIpDUJj4mQkBAGDBjA0aNHqVy5MrNnz8bZ2Zm4uDju3r3LyJEjuX79OunTpyd//vxMnDgRe3t7rSKTVCXhBYmEIa1jx45Urlz5lddr3JA3JWFf+6uQ9jKdf0XEWijriSQ9ZT1Ja5T1xFIp61kO3doU+Zf+aYCM3+d56NCh2NjY0L1791cKeGuQFflTwsnA2LFjefbsGQEBAQwbNozDhw+zdu1amjVrhouLC7ly5SIgIIAHDx7g5OSEi4uLVpGJRfurrRwSbvNQtWpVAGbPnk1gYCAxMTHmn8XTuCFvio2NjblvxtcLWLhwId988w12dnaUKlXqlfconImItVDWE0laynpizZT1JLVR1rMcOupF/satW7eIiIgAXgy2Cf/7Og0bNmT8+PEsWbKEzZs3v5E2iqRW8RPPkydPcuzYMT777DPs7OwYP348ZcqUYdWqVWzZsoXIyEjze7Jly4arq6t5kqtwJpbm9OnTPHv2DIPBQHR0NPDquBHffwGqVq1Kr169uHTpkrnIt0hyi4uLe+3PE/bNevXq0blzZ37//Xd8fX25cuXKm2yiiEiyU9YTST7KemKNlPUkNVDWs2y6GSfyF54/f863335rHjCvX78O/HPR4AYNGhAQEECrVq2Su4kiqd7KlStp37499vb2lC9fHngR3GbNmkWhQoUIDAxky5YtPHv27JX3qoCsWKKDBw8ybtw4AG7evAm8vq8mnAhXqVKFadOm4enp+eYaKmnOtWvXWLJkCfDnKsfXXXR+OaS1bNmSXLlykT9//jfWVhGR5KasJ5L8lPXE2ijriaVS1ks9VDNO5G+0b9+eM2fOUL58eeLi4pgzZw729vb/emKobRVE/l5ERAQtW7bk0qVL+Pn58emnnyaaOPTp04cjR44wceJEatasmcKtFfl7sbGxzJ07lz179hAbG8utW7c4efIkRqPxL8eCl7c40b7sklxOnDiBt7c3n332GU+fPuWTTz6hQoUKf/n6122/o7oWImJNlPVEkpeynlgTZT2xZMp6qYf+D4u8Rvw96sDAQNKlS0dwcDCVK1fGwcHhf1qhpXAm8iej0Zjo77Gxsbi6urJmzRoKFCiAn58fx44dM7/OYDAwY8YMWrVqRbVq1VKiySL/Ezs7O3r16kWmTJm4ceMGVapUwcbGBjs7u7/dKiIhhTNJLgULFuTTTz9l7dq1LFu2jAwZMgCvnpvjJVw1GU/hTESsgbKeSNJT1hNrp6wnlkxZL/XQ/2WRl8SvDnj+/DkPHz7EYDBQrFgxFixYwM6dO837QovIv5dwhc3mzZuZPHkygwcPZu3atTg7O7N+/XpsbW0ZNWoUx48fTxTS+vfvj62t7V9OcEVSWvwkNjY2locPH5I9e3a++OIL/vjjD4YMGcLz58/VhyVFGY1G0qdPj5ubG5GRkXh4eLB9+3bzufnvQpqIiDVR1hNJesp6Ys2U9cTSKeulLtqmUiSBhJPImJgY7O3tzb/r0KED58+fZ+TIkVSrVg1HR0fz7173eK+IvGrKlCls2rSJUqVKERUVxffff8+nn37K+PHjsbGxoXHjxjg4ODB48GAqV66s40osXsJxIyIiAldXV+DFuDB79mz27NlDyZIl8fHxwcnJKSWbKmnQy1uNnD59GoC9e/eyb98+PvjgA7y9vV/7WhERa6OsJ5K8lPXE2ijriSVT1kuddDNO5P9LGLKWLVvGjz/+SM6cOalUqRI1atQAXoS0ixcvMmLECCpVqsS1a9coXbp0SjZbJNU4cOAAo0aNws/PjzJlygBw6NAhvv76a+rXr8+4ceOIiIigatWqVKtWjSlTpqRsg0X+B/Pnz+fgwYNERETQvn17mjZtyvPnz1m4cCF79+6lRIkSDBgwgAsXLlCpUqWUbq6kAQkD19GjR4mMjCRv3rwULFiQkJAQAgICOHToEB999BGDBg1K4daKiCQvZT2R5KWsJ9ZMWU8sjbJe6qWbcSIkDmd+fn4sW7aMChUqcO3aNZydnWnfvj2NGjUCXhT6PnXqFJkyZeLtt99m7ty5WtEl8i8sXbqUAwcOsHjxYkwmEyaTCRsbG7Zv346npycLFy6kcuXKPH/+HHt7e+2nLhYt4eR35syZLFu2jPr163Pnzh3279/PoEGD6Nixozmkbd26lRs3bpAvXz527typcUPemMmTJ7N69Wrs7Ox49uwZY8eOpVGjRjx58oSAgAAOHDhA8eLFefLkCW3atKFq1aop3WQRkSSlrCeS/JT1xJoo60lqoayX+qjisAh/7pP722+/cfr0aQICAihXrhynT59m3rx5BAYGAtCoUSMCAwPx9/fn+fPn9O7dW4OsyEuCg4O5desWjx8/pmjRolStWhV7e3siIiK4efMmjx8/JnPmzOa910uWLEmGDBkIDw8HIF26dADExcUppInFig9nly5dIiIiAn9/f9577z2eP3/OokWLmDx5MgAdO3akS5culCtXjtu3b9O4cWNzsWSNH5IcEvatH374ge3btzNv3jxsbGzYu3cvQ4YMwWQy0bhxY7p27Yq9vT0//PADkZGRVK5cOYVbLyKS9JT1RJKOsp6kBcp6YqmU9VI/3YwT+f82bdrErl27ePbsGUWLFgWgRIkSdO7cmYCAAAIDAzEYDDRs2JAePXqY3xcbG4udnQ4lEYBu3brx4MEDnj59ysOHD6lTpw4ff/wxAIULF+bp06ds2bKFRo0akTFjRgBsbW3Jnj07mTJlSvRZCmdi6Q4ePEjfvn1xcXGhfv36wIsLDB07dsRkMuHr64vBYKBDhw6JtivRuCHJKT6crVu3jsuXL9O4cWMqVKgAQJEiRTCZTAwdOhSAxo0b06NHDzp06EDGjBkxGAzqnyJilZT1RP47ZT1JS5T1xBIp66V++r8v8v/FxcVx7do17t27x5kzZ8wnszJlytC1a1cWLVrElClTyJIlCx9++KH5fTqJibzQrVs3Hj16hJ+fH1myZMHZ2Zn79++bj5FPPvmEAwcO4OfnR1hYGB999BHp0qVjypQpODs7895776XwNxD53+TIkYN69eqxceNGfv/9d0qWLInRaMTZ2ZlOnTphY2PDxIkTyZ49O3Xq1DG/T+OGJLcHDx7w3XffsX//fr744gvgxSrK9OnT06tXLwwGA8OHD+f58+e0bNkSBwcH4MWWPOqfImKNlPVE/htlPUlrlPXEUinrpW6qGSdpUsL9nxM6ePAgkydPJmfOnPTo0YNy5cqZf3fs2DGCg4Pp06ePVnGJvGTnzp0sXbqUKVOmkCtXrr997bRp09i1axc3b96kSJEiuLi4EBgYiL29vbYrEYv1V+PGvXv3GD9+PHv37jXXwojfOuLp06fs3r2bBg0aaNIryep1W+GcO3eOuXPnEhwczNKlSylVqpS5H4eHhzN+/Hhu3rzJihUrUqjVIiLJQ7GSwMYAAKwwSURBVFlPJGkp64m1U9YTS6asZ110M07SnISDbFBQEPfv3+fq1as0adKE4sWLExwcjJ+fHzlz5qRLly6ULVv2lc/QJFIksWnTpnHx4kXmzZv3l68JCAjAYDDQuXNnLl++zKNHj0ifPj1FixbFxsZGj8uLxUo4bmzcuJHr169z7do1ypUrx+eff05MTAwjR440h7RKlSq9EujUvyW5JOxrDx48MNdqyZYtG3fv3sXb25sTJ06watUqihYtan79s2fPSJcuHTY2NqprISJWQ1lPJOkp64k1U9YTS6asZ31eve0vYuXiT2K+vr5MmDCB7777jtOnT9OsWTNmz55NlSpV6N69O3fv3mXRokX8+OOPr3yGwplIYr///jsuLi4AxMTEvPJ7k8nE9evXWb16NbGxsRQqVIiKFStSvHhxbGxs9Li8WLSE48bUqVOJjIzEycmJGTNm8PXXX5MpUyYGDhzIJ598QteuXTl48OArKyvVvyU5mEwmc1+bNWsWvXr1onnz5vTs2ZNevXqRPXt2fHx8KFu2LK1ateL8+fPmQObs7Gw+/yqciYi1UNYTSXrKemLNlPXEUinrWSfdjJM0adOmTWzcuJHZs2ezcOFCBg4cSFxcHOXKleP+/ft8+umnfPXVV5w+fZpDhw6ldHNFLJ6zszOnT58GwN7eHqPRaP5d/OBft25dHj16xB9//JHo98Brt4QQsSQHDhxg586d+Pv7M2TIEGrVqoXJZKJFixZcuXKFnDlzMmjQIN577z0WLFiQ0s2VNCI+WPn7+7Ny5Uq6du3K7t27yZUrF3v37uX8+fMUKFCAESNGULZsWRo1asSNGzcSBTKdf0XE2ijriSQtZT2xdsp6YomU9ayT/kUkTXh5Mnjr1i1q1qxJsWLF2LZtG127dsXHx4ccOXLg7e3No0ePqFWrFpMmTaJfv34p1GqR1KNx48bcv38fX19f4MWAHxcXZ/4zwMWLFylSpAg5c+bUhEAs3svjxoMHD3B3d6dUqVLs2rWL/v374+npSdmyZfH19eXQoUO89dZbjB07lmXLlqVQqyWtiN9l3mQyERISwqFDhxgxYgTVq1fn8uXL7N+/n2nTphEZGcm3335Lnjx5GDBgAB06dPjHWi8iIqmNsp5I8lLWE2ujrCeWTFnPummEFKuX8LHew4cPYzKZuHnzJqGhoRw7dozhw4fj6elJ69atcXV15ccffzRvV/L+++9ja2trnmiKyOvlz5+f2rVrs2PHDnMtgYRb/Dx//pxDhw5RpEgRHBwcUqqZIv9KwnFjx44dPHnyhMePH+Pg4MD+/fvx9vbG09OTVq1akS5dOn799VeuXr0KgLu7u3k7CJHkkHCrkZiYGGxtbXn8+DFvv/02+/bt4+uvv2bgwIHUqVOHoKAg1q1bx/PnzylWrBiDBw/Gzs6O2NjYFP4WIiJJQ1lPJPkp64k1UdYTS6asZ/20qa1YtYSFLv39/fn2229ZuHAhn3zyCePGjSMoKIjhw4fTvHlzAEJDQ8mVKxe5c+dO9DmqGyDy9zJnzkyXLl14/Pgxy5Yt4/Lly3Tv3h07Oztu377NsmXLePDgAfPnzwdQAVmxWAnHjblz5zJv3jw2b97Mp59+ir+/P0eOHGHy5Mk0aNAAeDFBft24oRXBkhwSXjyYPHkytra2fPXVV0RHRzN58mR++eUX88UDADc3NwwGwysXDFTXQkSsgbKeyJuhrCfWQllPLJmyXtqgfx2xavEnsV27dnHt2jXGjx9PgQIFcHFxoUSJEly+fJnnz58TGRnJH3/8wbRp08iaNSslSpRI4ZaLWKaEk1eAuLg4bG1tMZlM5M+fn2HDhrF9+3aWL1/OoUOHCAsLo2TJkuTMmZMNGzZgZ2dnfo+IJYrv33v37uX27dvMmTOHfPnyYTKZ8PT0ZMqUKfz222/kzp0bo9ForhlQs2bNlGy2pBHxF7Z++ukndu3ahY+PD66urvTq1YvRo0fzwQcf0KpVK0wmEzExMRw+fJj8+fPj7Oycwi0XEUl6ynoiSUtZT6ydsp5YMmW9tMFgit+IVMRKnT9/nq+++oqQkBD8/f356KOPALhy5Qr+/v4cPXqUiIgIcuXKRcaMGVm2bBn29vaaRIr8jc2bN9OwYcNEP0u4AjI6OprffvuNyMhI8ufPT+7cuTEYDMTGxmqVjlg0k8nEkydPqFSpEgC9evXi66+/BuDRo0fs378fPz8/oqKiyJYtG2+99Rbz58/XuCFvzIIFC9iyZQuFCxfGz88PgPv377N69Wr8/f2pUqUKzs7OPHz4kNDQUDZs2IC9vb1WqYuIVVLWE0l6ynpirZT1xNIp61k/3YwTq/PyCejx48cEBQUxbdo03nvvPWbOnJnodyEhIZw9e5ZcuXJRunRpbG1tNYkU+Ru3bt2iRYsW9OrVixYtWrzy+5dXVP7Tz0VS2uv65rVr12jbti1Zs2Zl5MiRlClTxvy7kJAQbt26haurK/nz58fGxkbjhrwxP/30E19++SX29vYsXLiQcuXKAfD06VN++uknVq1aRfr06cmdOze9evUy1w1Q/xQRa6CsJ5K8lPXE2ijrSWqirGf9dDNOrErCQfbGjRu4uLiQJUsWjEYjGzZsYOzYsdSqVYtJkyYBvHZli1a7iPy9Z8+e4eXlhbOzM5MnT07p5oj8JwnHjTNnzmAwGMiQIQO5c+fm8uXLtGjRguLFi+Pt7U2xYsX+8TNEktLLfSs6OhoHBwdOnDhB27ZtqVSpEl5eXhQqVMj8mpfnMZrXiIi1UNYTSX7KemJNlPXEkinrpU26GSdWI+FJbPbs2ezatYuQkBA+//xzWrZsSc6cOfn2228ZPXo0devWZeLEiYBOXCJ/568edf/ll1/o0KEDM2bMoFq1ainQMpH/LuG44efnx4YNGwDImjUrY8aMoUSJEly6dImWLVtSokQJBg8eTNGiRVOyyZKGJOyf69at48KFC9ja2tKmTRs8PDz4+eef6dixIx9//DH9+vWjYMGCgOY1ImKdlPVEkp6ynlgzZT2xZMp6aZdu7YvViD+J+fr6EhgYSNu2bWnRogVr165l8eLF3L17l88//5wRI0awe/duunfvDqCTmMhrrFixgnPnzpnD2fbt29m7d6/592XKlOGTTz4hODiYuLg4jEZjSjVV5P8sYThbvXo1I0aMwMfHh7i4OAYNGsTp06cpXLgwq1at4ty5c3h5eXHjxo0UbrWkBSaTydw/J02axJQpUzh//jxHjhyhT58+3L59m/fee4/Fixdz8OBBZsyYwcWLFwHNa0TEOinriSQdZT1JC5T1xFIp66VtuhknVuXIkSPs3buXpUuX0rx5c2rWrEloaCjbt28nICCA+/fv07RpU/r3709ERIQmlSKv8eOPPzJmzBiWL1/OhQsXePz4MWPHjmX06NG0bduW77//nsjISBo0aMD27dt58OABNjY26EFrSY3OnTvHwYMHmTdvHjVr1sTNzY179+5hZ2fHgAEDOHfuHIULFyYwMJBs2bKRO3fulG6ypAHxF8dWrFjB1q1bWbhwIcuXL+ezzz7j7Nmz9OrVixs3blChQgUWL17Mnj172LZtWwq3WkQkeSnrifx3ynqSlijriSVS1kvbdDNOrMqjR4/IlCkTBQsW5Ny5c/j5+TFlyhR69uzJypUrCQgI4Ndff6Vt27YsXboUGxsbhTSRl1SsWJGJEydy6NAhlixZgslkYteuXUydOhWj0cjo0aNp06YN9vb2FCxYkAULFhAXF/faLU5ELN2TJ0+4e/cu7u7uXLt2jcDAQHr06IG3tzdhYWEMGDCAPXv2ULRoURYtWoStrS1xcXEp3WyxciaTidjYWI4dO0anTp0oWbIkZ86cYd++fXTo0AFHR0f69+/PnTt3eO+999i8eTO9e/dO6WaLiCQrZT2R/05ZT9ISZT2xRMp6aZtuxkmqFb8yy2Qymf8cFhZGpkyZiIiIYPfu3RQoUID33nuPJk2akD59eoKCgli3bh3wYiVCwkeDRQTzBYtGjRrRr18/Dh06hK+vL48ePaJChQqsWLGCQYMGUbp0aXr37s3Nmzf56aefCA8PB9CKSbFor+uf6dKl49NPPyUqKoqgoCCyZctGjRo1qFChAlmzZiUsLIxvvvkm0VijrSEkuRkMBgwGA48ePeLJkyfcu3eP1atXU7NmTQYPHkyFChU4c+YM1apV49ixYxQpUgQ7OztiY2NTuukiIklCWU8k6SnriTVT1pPUQlkvbbNL6QaI/F8kLHQZGRlJdHQ0mTJlonXr1lSpUoWYmBj27dvH119/Tfbs2bl8+TKlS5emUaNG1KlTx/w5Wt0l8qf44yq+kHfjxo2JjY1lxowZGAwG2rZtS7FixahevTrVq1enUaNG/PLLLyxYsIClS5fSu3dvHVNisRKOG3fv3uXp06e4u7vz7rvvUqBAAeLi4vj2229p3749uXPn5t69e2TNmpWhQ4dSsWJF80U9keSQsH/Gs7W1pVOnTmTLlo1Lly7x6NEjGjVqBED27Nn55JNPKF68OGXKlDG/x85OU3sRSf2U9USSnrKeWDNlPbFkynqSkP4VJVWKP4nNnTuXAwcOcPfuXfLnz89XX33Fu+++y+nTp7l16xbly5cnIiKCqVOnYm9vT926dTEYDK89EYqkZVFRUTg6OgJw9epVnj9/zjvvvEOzZs2wsbHBz88PgPbt21OkSBHgRWHvMmXK4OzszN69ewkPD8fV1VUhTSxSwgLe+/fv59q1axQuXJhKlSoxYMAAnjx5QkxMDM7Ozty8eZNJkyZhMpl47733NG5IskrYt3bs2MGtW7eIiYnh/fffp2rVqgAMHz6cp0+fUq5cOQAOHTpEoUKF6N69OwCxsbEKZyJiNZT1RJKWsp5YO2U9sVTKevIy/UtKqpLwJBYYGMjixYvp1asX9vb2fPvttwwdOpTevXtTuXJl8uTJQ7Vq1ciTJw+2trasX79eg6zIS2bPnk3Pnj3N4WzatGls2LCBp0+fkj9/fubPn0/Tpk0xGAxMmzYNg8FAhw4dKFy4sPkz0qVLx9WrV4mOjlY4E4uT8Jy/Zs0avv32W3x8fHB1dWXfvn3s27eP+/fv4+vrS+HChRkxYgRZsmQhc+bMrF69GltbW40bkmwSbqE2depU1qxZQ4kSJbh48SJbt26lcuXKjBgxgqxZs3Lw4EEmTpzIqVOniIiIYM6cOebPUDgTEWugrCeStJT1xNop64klU9aT1zGY9ByupELff/89v/zyC3nz5qVBgwbmn3ft2pVr166xaNEiHBwc2Lt3L46OjjRp0sS8v65OYiIvnDhxghYtWvDBBx+waNEiduzYwZgxYxg+fDgRERGsWLGCyMhIvvnmG9zd3dmwYQMzZsygVKlSeHl54eHhwf3791m0aBHbt29ny5YtuLm5pfTXEnmt77//np9++glXV1e6dOkCwNOnT1m3bh3Lly9n0KBBfPLJJxw4cAAHBwcqVqyIra2txg15Iy5dusTAgQMZPnw45cqVIzQ0lMDAQLZs2cIXX3zBl19+Sffu3TGZTLi6uuLr64u9vT1xcXGqayEiVkdZT+S/U9aTtERZTyyZsp4kpJtxkuqcPXuWjh07EhoayoQJE2jcuLF52wWj0cjHH39MkyZN6Nu3b6L36SQmklhUVBQHDx5k1KhRFCxYkEqVKpE9e3aaNm0KvJgweHl58ezZM5YsWcJbb73FihUrOHToEP7+/tjY2PD06VP27t1LyZIlKViwYAp/I5FXmUwmHj16xIcffghAx44dGTRokPn3MTExtGvXDnd3d6ZOnZrovRo35E2YP38+R48eJTY2ljlz5pAxY0YAHj58yOzZszl16hTr16/HaDQSGxuLg4MDoO1KRMQ6KeuJJA1lPUkLlPXE0inrycv0HK5YvJfvF+fMmZM+ffqQOXNmfvrpJwAcHR2Jjo4GoGDBghiNxlc+R4OsyJ/i4uJwdHSkatWqjBgxgps3bzJjxgxiY2OBF8dd4cKFmTx5Mi4uLnTq1Ilbt27RunVr5s6di42NDXFxcbi4uNCwYUOFM7Eo8WNAfIH6rFmzsnnzZjJnzszx48e5ffu2eWyxt7fnnXfeIS4u7pXP0bghb0KRIkX44YcfOHXqFHfu3AFe9N2sWbPSpEkTzpw5w6+//oqNjY05nGm7EhGxFsp6IklPWU+smbKepCbKevIy3YwTi2Y0Gs37koeFhREREUGmTJlo1aoVPXv2ZO/evUyePBkABwcHDAYDT58+Na80EJFXmUwm88QzJCSETz/9lCFDhuDu7s62bdsAMBgMiUJaRESEubD3y5+h2gFiSRLu+f/777/zxx9/cO/ePYoUKcKSJUu4dOkS06ZN4+bNmxiNRp4/f87p06dxd3dP4ZZLWvDyBeT4pzyWL19ObGwsy5YtIyQkxHxedXR0pHjx4q9sC6XzrohYA2U9kaSnrCfWTFlPLJmynvwb2qZSLFb8KhcAf39/fv75Z65evUqZMmX4/PPP+eijj1ixYgVTp06lbNmy5MyZk4cPH3L16lV27NihVQQir5Fw8hocHExAQAB9+vShfPny7N27l2HDhvHOO++wePFi4M/j8NatW7i7u2v1mKQa06dPZ8+ePYSGhgLQvXt32rRpw8WLF2nevDlubm7kz58feLFFxNq1a80r0USSQ8J5zfbt2/n9998JCQmhfv36vPPOO/z000906NCBunXrUqtWLbJly8bs2bMJCwtj5cqVKiwvIlZFWU8k6SnrSVqhrCeWRllP/i3djBOLlHASuWTJEubOnUvfvn25e/cuFy5c4Pvvv8fX15datWqxYsUK5s6di8FgYMKECea9orX/s0hiCY+rHTt2sH37dg4ePMi7775L3759KVeuHEFBQQwdOpQSJUqwaNEiIPGkQseVWKqE/XTHjh2MGjWKcePGYTKZ+O2331i4cCFffvklXl5enD9/nvbt22M0Gunbty8tW7bExsaG6OhohTRJFgn758SJE9m6dSseHh6EhYVx/fp1+vXrR5cuXfjhhx/o1KkTcXFxVK1aFXt7e2bOnImNjU2ic7iISGqmrCeS9JT1xJop64klU9aT/4WWk4lFij8BXbx4kVOnTjF48GAaN24MwLVr1/jmm28YPXo0efPmpUmTJtjY2DBp0iT27t1rDmgiklj8ceXr68umTZto2LAhX3zxBYcOHWLu3Ll07tyZmjVrAjB8+HAaNWrEpk2bEj0ir3Amliq+n+7Zs4cffviBjh07mvvzJ598Qs6cORk7dizvvfce1apVY+nSpbRo0YL9+/dTuXJl8ubNq3AmySa+f164cIHz588zf/583n77bWxtbZk5cybTpk3Dzc2Npk2bEhgYSIcOHXB2dqZ3797Y2NhgMpkUzkTEaijriSQ9ZT2xZsp6YsmU9eR/oX9psVhHjhyhRYsWfPfdd4lOSvnz56d169ZkyZKFEydO4OTkRN26dfHy8mLLli0MHDgQ0ERSBODx48eJ/n727Fn27NnDjBkz8PLyYvjw4YwbNw47Ozvmz5/PL7/8Qs2aNRk6dCjZsmV7Zc9rEUt25coVli5dyrfffmsuUB8bG4vRaKRNmzZUq1aNdevWER0dTZEiRVi1ahUnT57E29uba9eupXDrxdrt3LkTT09PHj16hLu7O3Z2dtja2tKvXz9atWrFlClTePDgAeXLlycgIIDdu3czZ84cLl++rLoBImJ1lPVE/jtlPUlLlPXEkinryb+lm3FiceJ3Tq1cuTJffvklMTExHDt2jJCQEPNrihQpgrOzM9evXwcgQ4YMNGjQgD59+nDkyBEePHiAdmCVtG7AgAGMHDky0c9MJhORkZE4OTmZf1ahQgW+/PJLfvvtN/z8/Dh27Bh169YlICDA/Li8iCWL76MFCxakTZs2FC9enK1bt3Lv3j3s7OzM40HGjBlxcXHBwcGBuLg4ihYtyuLFi7lz5w7Ozs4p+RXESsX3PZPJxJMnT3BwcODu3bvY2dmZt8sBaNiwIQB3794FoFKlSixevJht27bxzTffEBMTkzJfQEQkiSnriSQNZT1JK5T1xFIp68n/hW7GSYobO3YsmzZt4tGjR8CLx3vjT0Q9e/akc+fOHD58mJ07d5qLsz59+hSAvHnzmj/H1dWVZs2asWvXLrJly6aVBZLm9e7dm8mTJwN/HjPR0dE8ffrUvIoyfnJQoUIFChQowO+//05gYCDnz58H0OPyYpH69u3LnDlzCAoKAkjUR2vVqkW3bt3Inj07w4YNIyQkBFtbW2JjY/njjz/Ili2b+T1xcXGUKFGCvXv38tZbb6XIdxHrc+HCBfN8JX4uYjAYaNasGR07diRLlix4eXkRHh5u3i7HwcEBNzc388Uzo9HI+++/z7Jly/jyyy+xt7dPmS8jIvIfKeuJJA9lPbFWynpiyZT15L8ymLSkTFLQhg0bGDJkCPBigliwYEF69OiBi4tLopUrkyZNYvv27RQrVowCBQpw7do1bt++zcaNG7G3t09ULFMkrVuyZAnlypWjZMmSAKxcuZIFCxawdu1asmfPzoABAzh8+DArV66kYMGCAISFheHl5cU777zD5s2b6dChA23atEnJryHyWgcOHKBbt24UL16cJ0+ekD9/furXr88nn3yCi4uL+XU7duwgMDCQ33//nSJFiuDi4sKFCxfYtm3bK5NdjSGSVHr37s2ePXuoWbMm5cqVo1mzZri6upp/Hxsby7Zt21i3bh2Ojo7079+fyMhI5s+fz/Pnz1m6dKn5goOKeItIaqesJ5L0lPXEminriSVT1pOkoJtxkqJu3rzJ+PHjyZ07N0+fPiU4OJiYmBgqVKhA69atKVq0KJkzZwZg5syZ+Pv7U6RIEapVq0bfvn2BFyc7Ozu7FPwWIpbjxIkTtGzZknr16tGxY0eKFy/O2bNn6du3L87OzixYsIDnz5/j4+PDb7/9Rvfu3XFwcCA4OJjQ0FA2bNhAv379iImJYfbs2Sn9dUReq23btsTExNCtWzemT5/OjRs3yJ49O23btqVUqVKUKlUKgODgYKZPn87t27fp168fLVu2BDRuSPKJD2jt2rVj3bp15MiRg4oVK9KlSxcyZcqEq6sr0dHR7Nq1i5kzZ3L79m0++OAD8uTJg5eXF05OTgpmImI1lPVEkpaynqQFynpiqZT1JCnoX19SVPyj4rdu3cLT05MNGzZQo0YNLl26xJdffomXlxfz588nLi6O3r17M2TIEPOWC2FhYQAaZEUSKFOmDNOnT+enn35i0aJFnD9/nuLFizNr1iyioqLo1q0bjo6OzJ49m5YtW7J9+3a2bdtG5syZWbVqFQBxcXG8/fbbKfxNRF4VFxcHQP369QkLCyNDhgysXbuWvn378vbbbzN27FjatWvH+PHjOXLkCFWqVKFHjx4UK1aMdevWJdoiSyQpxa9t69WrF/nz58fd3Z3169dTsGBBdu7cSePGjRkyZAgHDx7E3t6eBg0aMHjwYEqVKkVoaCh9+/bFycmJ58+fK5yJiNVQ1hNJWsp6Ys2U9cRSKetJUtKTcZJi4lcDXLx4kc8//5yePXvStWtXAH755RfatWtHhgwZCAkJIU+ePLz99ttMnz6dmTNnsnXrVj799FM6d+5s3hNaJK1LuP3Cjh07mDhxIu+99x6dO3emWLFiXLhwgT59+pAuXToCAgLIli0bERERwIt6AkajkRUrVrBy5cpE25qIWJrbt2/TvHlzqlWrxtixY80/r1ixIm5ubty9e5fIyEgKFizIuHHjePDgAYsXL+bBgwesWLGCHDlypGDrxZqFhIQwcOBAABYvXkx4eDihoaHMmTOHjRs3AlCuXDk++eQTqlWrxvHjxwkMDMTNzY1p06aZnxAREUntlPVEkpaynqQVynpiqZT1JCnodqykmPjVAO7u7lStWpWtW7eaV0COHDmSypUrM3fuXGbOnEnOnDl5+PAhdnZ29O/fnxo1anDo0CFsbW1T8iuIWBSDwYDJZCI2NpY6deowZswY9u/fzzfffMP58+cpUqQIM2bMIDo6ms6dO3Pv3j1cXV25e/cubdu2pUOHDuzYsYNvvvlG4UwsltFoJHfu3Hz55ZesX7+eS5cuAdCgQQMKFy7MokWL+Pbbb+nYsSOFChWiTJkyfPLJJ7Rt25Y8efKYC9mLJAc3Nzdat27NkSNH2LJlC+nTpyd37tycO3eOypUr8/XXX3Pv3j0mTpzIggULqF+/Pl26dOH69et4e3ujNXIiYi2U9USSlrKepAXKemLJlPUkKejJOLEIe/fupVevXkyYMIElS5bg6urKzJkzyZIli/k1LxddDQkJwc3NLSWaK2Ixli9fzocffki+fPkAiImJMRcs9vLy4vvvv8dgMJj3sS5atCgXLlygXbt2VKtWjYkTJwJw8OBBsmTJQvbs2cmePXtKfR2Rf+3kyZP06tWLjz76iGPHjpE5c2bmzJljHhcSHgvxnj59mqjwt0hSM5lMRERE0KNHD2xsbJgwYQLdu3cnffr0zJo1i8yZMxMSEsKlS5d49913cXBwICYmhqCgIEqUKIGHh0dKfwURkSSnrCfyf6OsJ2mVsp5YImU9SQq6GScWo0OHDvzwww9UqFCBOXPmkD59euDFvtHxqyKNRiOA9tgVAU6dOkWzZs1o3LgxPXr0SDSw9+rVi+vXr7Nu3ToOHz7MqFGjqFChgjmk3bx5k1y5cmnFsaRqI0aMYM2aNXz44YfMmTMHR0dH4NULei//XSS5BQQE4Ofnh7OzM6VLl2bChAlkz579lb4YHR2Ng4NDCrZUROTNUNYT+d8o60lap6wnlkpZT/4LzXLFYlSpUgVbW1saNmxI+vTpzWEs4QTSxsZG4Uzk/ytZsiT+/v5s3ryZ2bNn8/DhQwB69+7N9evX8ff3J126dNSsWZNhw4Zx/PhxpkyZwo0bN8iTJw+2trbmIskiqUn8+NC0aVPc3d3JkSOHOZzBq0W7Fc7kTYlf49axY0dKly5NunTp8PX1Na9Cf7kvKpyJSFqhrCfyv1HWk7RKWU8slbKeJAXNdCXZxQ+kfyX+ZNamTRvy58/Pjh07AK2IFPk7JpMJk8lE9erVmT17Nps3b2bmzJl069aNa9eusWDBAjw8PMzH32effUa/fv1wcHBItKpSqyXFEv3VuBF/QSF+fChatCj58+fn5MmTREVFvbH2SdoWP29JuLlE/J/j67mYTCbKlStHZGQk58+fB/55PiQikhop64kkPWU9sWbKemLJlPUkuWmbSklWRqPRPJDeuHGD0NBQMmTIQMaMGcmcObP5Ed741y1cuBA/Pz+WLVtG2bJlU7j1IpYv/hjat28fX3/9NXZ2dixZsoTy5cubfw+vrtBJeGyKWJKEffPXX3/lwYMHPHv2jCpVqiSqHRP/uhMnTtCiRQumTZtGnTp1UqrZkkYk7J+xsbHAn09yvHxe/f3332nSpAn169dn2LBhKdJeEZHkpKwnkryU9cTaKOuJJVPWkzfBLqUbINbLZDKZT1QzZswgKCiIx48f4+LiQvbs2Rk6dChFixYF/lz5UqlSJY4ePUrp0qVTrN0iqUn8ypwaNWqwcOFCOnfuzMaNG8mRIwceHh5/uWWDwplYqvi+OXXqVPbt24fJZMLZ2Zlhw4axePFiKlSokOh12bNnp3Pnznz66acp1mZJGxIGsBUrVvDrr79y+/ZtsmXLxqBBg8idO3ei1+bKlYsqVapw+fJlQPUsRMS6KOuJJD9lPbE2ynpiqZT15E3RCC3JJv4kFBAQwJo1a/D09OTw4cNUqFCB3377jYiICJ4/f25+vdFo5J133mHRokXa31zkfxAf0uILG69fvx5/f39u3bqV0k0T+T9ZsWIF69atY+zYsezcuZPPP/+c2NhYjEajedyI3wbC3d2dgQMHYmdnZ169JpIc4sPZlClT8Pf3p0iRIjRq1IgffviB7t27ExoaCiQOcp06dWLRokUp1mYRkeSirCfyZijribVR1hNLpKwnb4puxkmyMRqNREZGcvToUXr16kWVKlU4ePAg27dvZ8yYMdjY2LB27Vqio6OBV1dvaX9zkX8v4apJf39/tmzZwoQJE7h//35KN03kb23cuJGwsDDz3+Pi4jh79iwdO3akbNmyBAUFMXnyZMaNG0emTJnw8fEhLCzstSt+7ez0wL8krfg5SrxTp04RFBTEzJkz6dKlCzly5MBkMtG9e3euXr1KRESEeRsTeFHrwtbWFqPRqJWSImJVlPVE3hxlPUmtlPXEkinrSUrQzThJUglLEBqNRtKlS8cff/xB2bJlOXLkCH379mXgwIE0bNiQY8eOsXjxYsLDw1OwxSKW7+VCsDExMa99XXxIq169Or6+vjx+/JisWbO+iSaK/J/8+OOPeHt7M3fuXCIiIoAXF+fu3buHwWBg//79eHp64unpSdOmTfnjjz8IDg7m5s2bKdxySQt69erFrFmziIyMNP/s0aNHxMbGUq5cOfbt20f//v0ZMGAANWvWJCAggAULFgCv1m7RdlEiYg2U9USSnrKeWCtlPbFkynqSUrSsQJJU/Alp3bp1hISE8NVXX5EhQwb69u3LvXv38PHxoUmTJgBky5aNrFmzYm9vn5JNFrFoCR+BX7lyJZcvX+bXX3/l008/pWLFipQtWzbR6w0GA0ajkTp16pgLHKuAt1iqihUrMnHiRIYNG4bJZKJbt25kypSJXLlysWLFCp4+fYqnpyetWrUCIEOGDGTOnBlXV9cUbrmkBUWKFMHf3x9XV1fatm2Ls7Mzjo6OZM6cmSVLljBjxgwGDx5M8+bNef78Offu3SNXrlzAqwFNRMQaKOuJJC1lPbFmynpiyZT1JKVoxJYkFxsby969ezl48CAAPXv2JDY2lnz58tGkSROMRiPR0dFs2bIFd3d30qdPn8ItFrFc8cHK19cXf39/MmfOzEcffcSyZcsYM2YMT548+cv3xK9eVjgTSxRfK6ZRo0aMHDmSJUuWsGzZMgD69OmDs7Mzrq6ulC5dmoiICEJCQpg/fz65cuUiT548Kdl0SQPi4uLo2bMnXl5e+Pn5sXz5cqKioihWrBiPHj1i4sSJdO/enebNmwMvApm9vT1vvfUWkPjpERERa6KsJ5J0lPXEWinriSVT1pOUZDCpB8l/ZDKZzKsC4v985coVvvjiC0aNGkWtWrVYsWIF8+fPJ0OGDLi7uxMeHk5UVBTr16/H3t4+0WeISGI//PADQ4YMYcaMGZQsWZJffvmFjh074ufnh7u7O5kyZSJnzpwp3UyRfy3hOX/WrFmEhoayatUq4uLiaNu2LYMHD+b69et06dIFo9GIyWQia9asGI1G1q5di729vVYBS7KJi4sz1zK6ePEi/v7+BAUF0bt3b7p27Wquc1GsWDGqV69O1qxZWbt2LY8ePWLjxo2qZyEiVkVZTyR5KeuJtVHWE0umrCcpTT1I/rOEwSr+zzly5KBGjRoEBwdTr149mjZtStmyZc0Da86cOfnyyy+xs7MjNjZWJzORBF6eeIaHh+Pm5kbJkiXZsWMHQ4cOxdPTk/Lly9OnTx+aNGlC/fr1U7DFIv+b+LFi4cKFrFixAl9fXz788ENu377N+PHjARg6dChbt25lx44dhIaG8tZbb1GrVi1sbW01bkiyig9nkyZNIigoiOLFi1OoUCGmTZtGTEwMX3/9NYGBgYwYMYKFCxeSJUsWPDw8CAgIwM7OLlHAExFJ7ZT1RJKWsp5YO2U9sWTKepLSdHaTJDFv3jwuXLhAo0aNqFq1Kq6urtSsWZP+/fvTqlUrypQpQ8mSJSlZsmSi98XFxWmQFXlJfDg7ePAgFStWNG/bEBQUhI+PDwMHDqR169YA3LlzhwsXLiigSaoTFxfHsWPHaN26NR999JH55zlz5qR3797Y2dnRt29fmjVr9sr7NG5Icvv+++/ZvHkz8+fP55133sFgMLBy5UrGjBmDyWSiZ8+eBAYGEh4ejsFgIEuWLBgMBl08EBGrpKwnknSU9SQtUNYTS6asJylJz/zK/0nC3U2jo6PJli0b58+fZ8KECbRo0YJjx45RqVIlWrZsyeLFi3n69Olr99TVagKR1/v555/x8fHh+vXrfPbZZ9jb29OzZ088PT3N4Sw0NBQnJyfy58+fwq0V+WdGozHR3589e8aVK1eIiYkx/z42NpaaNWvSqlUrlixZwqRJk4iIiEj0Po0bkhxenqOEhoaSOXNmChQoYP5Z69atGTZsGHPnzmXJkiXExsaSLVs2smbNisFgwGQyKZyJiFVQ1hNJXsp6Ym2U9cSSKeuJJdHNOPmfGY3GRNuVGI1GmjZtyubNmxkxYgQuLi4MGTKEnj17cufOHcLDw82rCUTk3yldujTOzs4sWbIEZ2dnunfvTt68edm6dSs//PADu3fvxsvLC4CGDRumcGtF/ln8KuD9+/cTHh5O+vTpqVGjBps3b+bMmTPY2NiYX5MxY0aKFy/OhQsXcHZ2TslmSxrwcj0keDG3uXLlCg8ePMDGxobY2FgAPvjgA2xtbZk4cSJBQUGJPkfzHBGxBsp6IslPWU+sjbKeWCplPbE0BtPrlrCJ/IWE+5sHBgby22+/cfr0aSpXrky1atWoWrUqAHv27OHs2bMEBgYSGRlJnz596N69e0o2XcRivVw3IP7ve/fuZcqUKUybNo2CBQsSHBzMwoULOX/+PHny5CF37tzMmjULe3t77VstqcIvv/xC//79KVeuHGPGjOH3339n+PDhAAwbNox33nmHZ8+e0atXL+rXr0+jRo2AxBNokeSydu1ajh8/zrhx4zAajbRv3x47OzvGjh1L3rx5gRfbRc2aNYv33nuP+vXra3WkiFgVZT2RpKesJ2mFsp5YMmU9sRS6GSf/J35+fqxdu5amTZsSFxdHcHAw9vb2tGzZkubNm5tfd/nyZY4ePUrLli11EhP5BwcOHKBUqVJkyJABOzs7rl69Su/evalfvz5fffWVObhdvnwZNzc3MmfOrH2rJVWJjo4mICDAXCh5xIgRHDt2jLlz5/Lrr79SoEAB84r8DRs2YG9vr3Amb0R0dDSTJ0/m+++/56OPPsLb25vvvvuOOXPmmAt5GwwG1q1bR0REBKtWrdL5V0SslrKeSNJT1hNrp6wnlkpZTyyJbsbJ/+zkyZMMGjSICRMmUKZMGQDOnj3L3LlzuXfvHj4+PpQsWfKVFWA6iYn8tQsXLtCwYUMKFy5MmTJl6NmzJzly5ODbb79l8uTJrFy5kkKFCgGJV469fJyJWIqEfTNhn42JiWHRokVs376d0qVLM3z4cKKioti/fz/379/Hzc2NBg0aYGdnp3FDks3rzp0REREEBASwd+9eqlatyqBBg/jhhx9Yvnw5hw4dokCBAmTNmhV/f39dPBARq6WsJ5L0lPXE2ijriSVT1hNLprOe/M/CwsKIiYkhV65cxMXFYWNjQ/HixenevTtt27bl3LlzlCxZ8pUTnwZZkT+9PDkoUqQIhw8fZvXq1Rw8eJA6derQsmVLChUqRPXq1Tly5AiFChV65X0KZ2JpDh8+zIcffmjum+vWrePOnTv06NEDOzs77O3t+fLLLzEajaxfv56xY8cyaNAgGjRokOhz4uLiNG5Isonvn6dPn6ZEiRIAuLq60qVLF0wmk7lGgKenJ++//z63bt3Czc0NZ2dnrZIUEaumrCfy3ynribVS1pPUQFlPLJlGdvlbRqPxlZ89e/aM27dvExYWhq2tLbGxsZhMJooXL46Hhwd3795NgZaKpB4JQ9axY8fYs2cP27Ztw2Aw0LNnT9atW8dXX33FtWvXmDx5Mps2bWLNmjWAAplYtq1bt9K5c2dzf42KimLfvn3s2bOHJUuWEBcXB4CDgwM9evTgnXfeYcOGDQwYMIBnz54l+izVxZCk1qdPHzZt2mT++65du+jbty/Lli0z/8zV1ZXOnTtTuXJl1q9fz5QpU4iNjcXDwwMXFxcMBgNGo1HhTESsgrKeSNJT1hNrpawnlkxZT1IL9S75SwknkdevX8fR0ZEcOXLw8ccfU6pUKYYPH86ECRPIkycPAOHh4RgMBvPfReT14o8rX19ftm7dirOzM7du3aJw4cI0bNiQjh070rVrVx48eMCtW7eYPn06NjY22qZELF61atXo1q0bo0ePJi4ujlatWjFp0iTGjRvH1q1bMRqNdOzYEXt7ewBKlChBeHg4xYoVI126dCncerFmz549w87ODh8fH9KlS0etWrUoWbIkhQoVYsuWLdjY2NC6dWsAMmTIQPv27dm+fTtbtmwhU6ZMdO3a1fxZOg+LiDVQ1hNJHsp6Yq2U9cRSKetJaqKacfKP/Pz8WLduHS4uLpQrV47x48dz4MABZs6cidFopFu3bsTGxrJ161YePnzIt99+q1UuIv9g7dq1+Pv7M336dAoVKsSDBw+YOXMmV69epU2bNjRr1sy8R3VERESiVTqaHIgle/r0KQsWLGDBggUMHTqUNm3aEBoaypgxY7h06RL169enXbt22Nvb07dvX8qWLUv79u0B1cWQ5BUaGsqMGTNYu3YtkyZNom7duty9e5fRo0dz9+5dmjRpQps2bYAXF6b9/PyoXbs2n376qfqliFgtZT2RpKesJ9ZKWU8slbKepBa6GSevSFikcs+ePYwZMwZPT0/OnTtHcHAwBQsWZMaMGfz444988803HD58mLfffpu33nqLGTNmYG9vT1xcnEKayN8YMmQILi4uDB061Hy8XLt2jeHDh+Po6Mi8efOws7NLdDyqgKxYqpeDVXR0NHPmzHklpI0ePZpTp07h6OiIg4MDz549Y+vWra/0dZGklLB/hoWFMXXqVL799lsmTZpEvXr1uHPnDmPHjuXOnTtUqVKFTz/9lOnTp+Ps7Iyfn58ujomIVVHWE0l+ynpiTZT1xJIp60lqo5txkkjCE9CzZ8/47rvvePjwIR06dCAqKorNmzezcOFCihYtip+fH7a2tly9epVs2bLh6uqqQpci/8BoNBITE8Pnn39OxYoVGTZsGEajEZPJhK2tLUFBQfTs2ZOdO3eSP3/+lG6uyD96uS7GgwcPyJkzJ3nz5mX58uXMnTuXYcOG0bp1a8LDw9mwYQNXrlzB2dmZgQMHYmdnp4t6kmwS9k+TyURMTAzR0dH4+fmxevVqJk+eTN26dblz5w5Tpkzh6NGj2NjY4O7uzooVK7C3t1c4ExGroawnkryU9cTaKOuJJVPWk9RIs2gxM5lM5hPQggUL+OWXX/jxxx+pX78+sbGxODo6Ur9+fQAWL15Mz549mTlzJgUKFDB/hgpdiiT28sBuY2ODo6MjH3zwAdu2baNx48a88847GI1G82tKlChBlixZUqK5Iv+z+P49ZcoUtm3bhqOjI25ubowYMYJOnToRGxvL2LFjMZlMtGnThnbt2iVaFamLepJcEp5/v/nmG06dOsXVq1cZNGgQXbt2JS4ujkGDBmEymahXrx4jRozg7t27hIWFUbZsWWxsbNQ/RcRqKOuJJD1lPbF2ynpiqZT1JLVSjxMg8UksICCA+fPnU7duXfLly8f+/fupX78+ZcuWxcnJiQYNGmAwGPD19cXPzw8vLy/z52g1gcifEl70WLFiBdevXydjxox06NCBZs2a8euvvzJmzBh8fHx45513CA0NZe3atWTLlo306dOncOtF/r0NGzawadMmZs2aRdGiRXn48CEeHh4ANG/eHGdnZyZOnEh0dDRffvllovdq8ivJJf78G18PqX379ri5uREeHk6OHDkYOHAg9vb2DB48GBsbG+rUqUOGDBnM74+Li1P/FBGroKwnkvSU9SStUNYTS6SsJ6mVep0Af57Ebt68ydWrV5k7dy4VKlQgIiKCHj164OnpyZQpU3j33XdJly4d9erVw83NjY8//jhlGy5iweJXhPn5+bFq1Sry5MnDo0eP+OWXX/D396dv377MmjWL5s2bkzdvXgwGA3Z2dqxbt077VkuqEL/3/8mTJ/nggw949913AczhbNeuXZw6dYpu3bpx//59goKC6Nixo+oFyBtz/vx5goKCmD59OhUqVEj0u4sXL9KsWTNMJhP9+/fHzc2N999/3/x7bacjItZCWU8k6SnribVT1hNLp6wnqZFGfjELCgqiVatWHDx40LyNgqurK3PmzCFPnjx4enpy4sQJ4uLicHJyokaNGtja2hIXF5fCLRexLAm3IYmOjubu3bssXLiQlStXMnDgQB48eED37t0pU6YM8+bNY9SoUdSrV4/OnTuzfv167O3tiY2NVTiTVCM0NJSIiIhXfn7z5k3WrFlDXFwcgwcPZsWKFRgMBlSuVt6UqKgoQkJCcHJyMv8sJiaGa9eu0b9/f0JCQujXrx+enp6UL18+BVsqIpK8lPVEkoaynqQ1ynpiqZT1JDXS6J+GvTxA1qxZk+rVqxMSEkJwcDBPnjwBIH369Pj7+5MvXz7at2/PpUuXEr1PqwlE/pRwheOhQ4dYt24d58+fx97eHgcHBz777DO6dOnCw4cP+eqrrzCZTDRt2pTu3bvTqFEj80UPPS4vlijhxQf4c0VwkSJFOHz4MMeOHUv0+3feeYciRYpgZ2eHg4ODOZxptaQkh5f7J8CzZ88wGo3mOQ2Avb09+fPnx9HRkfPnz+Pi4kKnTp2ws7MjNjb2DbZYRCT5KOuJJD1lPbFmynpiyZT1xFroZlwaZTQaEw2QkZGRAIwePZrmzZuzbds2NmzYQGhoKPBi1eSMGTNo0aIFhQsXTpE2i6QG8eFs0qRJ9OzZk8DAQC5cuMD169eJiYnBzs6OOnXq0LVrVyIiImjZsuUrq8x00UMsUcKLDxs2bGD69OnMnj0bgG7dulGhQgX69u3L4cOHuXPnDmFhYSxZsoT06dPj4uJi/hyFM0kOCfvnvXv3+P333wGoVKkSJUqUYOTIkVy5csX8+oiICDJmzEj27NkTfY4ujomINVDWE0keynpirZT1xJIp64k1MZj0/HCak/Aktnr1ao4fP86VK1coUaIEnTp1Im/evAwdOpSjR4/Spk0bmjZtSsaMGRN9RlxcnCaRIgkkXAH2888/M2HCBIYMGUL69OmZP38+hw8fxtfXl8qVK2Nvb09cXBwbNmzg+PHjjBs3TseTWLSE/XvixImsWbOGPHnycPXqVcqUKcPcuXOJiYlhxIgRHDp0iIwZM5IxY0ZsbW1Zs2YN9vb2WiUpb8TMmTPZvn07ERERfPTRR0ycOJF79+7Rp08fbt68SceOHXFxceHAgQM8ePCAb7/9VudfEbEqynoiSU9ZT6yZsp6kFsp6Yg10My4N8/X1ZevWrTRq1Ij8+fPj7e1NpUqVmDNnDs7OzgwdOpQff/yRhg0b0rFjR1xdXVO6ySIWb8OGDVy6dImnT58yevRo4EUtgQEDBvDjjz/i6+vLBx98gJ2dXaKLJbroIanBzZs38fLyYuTIkeTMmZPr16/Tt29f8uTJw9y5c80T32fPnmFra0vNmjWxtbUlNjZWq9AkWSQ8jy5ZsgR/f3+6d+9OaGgoK1eu5P3332fq1KmYTCZGjhzJ+fPnsbW1JU+ePEycONF8wUznXxGxNsp6IklPWU+smbKeWBplPbFGuhmXhiRcqfLrr78ycOBAJk2aRPny5fn555/p3LkzU6dOJXv27BQvXhw7Ozt69OiBnZ0dM2bM0CoXkX9hyJAhbNiwgcKFC7N48WKyZcsGvAhpAwcO5Oeff2b06NFUr15dEwKxaCdOnKBkyZLmfrpmzRo2btxIxowZmTZtmnk7kuPHjzNgwABy5crFggULEm1TArr4IG/GTz/9xM8//8zbb7/NJ598gslk4tChQwwcOJD33nuPOXPmAC8K0NvZ2eHs7IzBYNDFAxGxGsp6IslPWU+shbKepCbKemJNVDMuDYiJiQES79386NEjMmbMSPny5dm7dy9du3Zl0KBBVK9encmTJ7N48WIA/P39mT59urkQq4j86XUFZMePH0+PHj24d+8eK1as4P79+wA4ODgwZcoUChcuzJo1azRhFYu2ZMkSWrRowb59+4iLiyM2NpaYmBju37/PjRs3zCHMZDJRrlw5pk2bxt27d/niiy94+vRpos9SX5ek5u3tzYEDB8zzkpMnT9KzZ0/mzp1rnusYDAY+/PBDfH19OXbsGD179iQ6OpqMGTPi4uJintconIlIaqesJ5I8lPXEWinriSVT1hNrp5txVm7q1Kn06tWLdu3asWvXLsLDwwFwcnIiMjKSRYsWMWjQILy8vGjVqhUxMTFERkby+PFj82fY2Ni8UgRcJK1L+Lj8L7/8wqFDh9iwYQMmk4nevXvTokUL1q9fz9q1a3nw4AHwIqQtWrSIBQsWpGTTRf5Rhw4daNSoEd7e3gQFBWFnZ0ejRo3o0aMHd+/excvLC/jzwl/ZsmUZP348+fPnJ126dCnZdLFyJpOJS5cuMWzYMH744QcAcufOTffu3XFycuLIkSPm19rY2PDRRx8xZcoUgoKCzCsm42leIyKpnbKeSPJQ1hNrpqwnlkpZT9IC3SK2Ym3btuXRo0cUKlSI33//HW9vbyZOnMhnn31Gzpw5SZcuHX5+fnTp0oWWLVsCmFcP5MqVK9FnxU9EReSF+GNi2rRpBAUFYTAYCA0NZf78+YwYMYL+/fsTExPD2rVrMRgMfP755+TIkQN7e3sgccATsRQLFiwga9asNGnShHHjxmEymRg8eDAmk4latWpRt25dTCYTY8aMwdbWlgkTJgAvJs0VK1akYsWKgLYrkeSxc+dOateuzfLly+nbty/9+/dn6tSpVK5cmaZNm2I0GpkyZQpOTk54enoCL87VH3zwAWvWrKFEiRIp/A1ERJKOsp5I8lHWE2ukrCeWTFlP0grdjLNSLVu2JCoqilWrVpEhQwYMBgNNmjRh+fLlfPbZZxQsWJAOHTrg6+vLuXPnWLduHRkzZmT16tUYjUZatGiR0l9BxOItWbKENWvWsGDBAkqXLs3GjRvx9vbG0dGRuLg4Bg0ahMlkYs6cOeTMmZOmTZua36twJpbo6dOnODk5ASQKYN7e3gDUqlWLevXqATB27FhsbGwYN27cK6vOFM4kqV2/fp1du3ZRu3Zt8wXmvn37MmDAAKZNm0alSpVo3rw5AL6+vtjY2DBgwADgxfm2dOnSAKobICJWQVlPJPkp64m1UdYTS6WsJ2mJZghWqFWrVkRFRbF8+XIyZsxoriNQvnx5smbNan5dw4YN6d+/P3FxcYwaNYp58+bh4ODAunXrsLOzIy4uLqW+gkiqcPHiRbp160bp0qXZuXMn48aNY/To0djZ2TF27FgABg8ezJAhQ2jUqFHKNlbkXyhdujTbtm3j9u3bwIuJ7YQJE/j000/x9vZm165dODk5Ub9+fYYNG8b69euZN29eCrda0gIbGxt++eUXzp49C7zYgm3GjBmUKlWK/v37c+TIEVxdXWnevDmenp588803jBw58pXPUTgTkdROWU/kzVDWE2ujrCeWSllP0hL1UivTvn17Hj9+zPbt27GxsSE6OhoHBwcAbt++jbu7OzExMebtE5o0aUL9+vW5e/cuLi4uZM6cGYPBoNUEIgkcPXqUhw8fUrJkSbJnz46zszNRUVGcOHGCQoUKcezYMYYMGYKXlxdffPEFR48eZd26dTRu3JhSpUrRpk0bQNs5iOXLly+feZ/23Llzm8eChKsmDQYDn332GXXr1iVLlixUqVIlhVstaUGePHmoUaMG+/fvp0iRIgCkS5eOGTNm0KdPHwYMGGDexqR58+Y8e/aMo0ePYjKZVC9ARKyGsp5I0lPWk7RCWU8slbKepCUGk8lkSulGSNJ48OABXbt2JTw8nBUrVpAjRw7z77y9vdm4cSOlS5fGxsaG9OnT4+HhQZUqVXBxcaF8+fLm12p/c5E/de/endOnT/PgwQOcnJzo0qUL7dq1w9XVFT8/P7777jtu3brF0KFDadasGQDfffcdvr6+LF26lGzZsqXwNxD53wwePJjjx4+zfft2HBwczCHNaDQyZMgQgoKC8PHxoWHDhub36KKevAkLFixgzZo1bN26FWdnZ3O/i4qKok+fPvz222/mbUwiIyNJly6duT6SQpqIpHbKeiJJT1lP0hplPbFUynqSVmgWbiV2795NtmzZmDp1KlmyZKF169bcu3cPgF69enHs2DE6duxIlSpVyJUrF3fu3GHnzp189dVXTJ8+nYT3ZBXORF5o2bIlDx48wM/Pj507d1K/fn0CAgJ49OgRAO+//z7h4eEULlyYt99+G4CQkBDWrl1Lnjx5Em0VJGLpjEYjAF9//TVOTk4MGjSImJgY7OzsiI2NxcbGhvHjx/Pee++xcePGRO9VOJM3oWvXrjg5OTFw4EAAc990dHRkxowZvPvuu3Ts2JFTp07h5OSkcCYiVkNZTyTpKetJWqKsJ5ZOWU/SCj0ZZwWuX7/OtGnTmDlzJkajkWvXrjF48GDCwsLInTs3Dx8+ZN68ebz11lvm9zx9+pTo6GhOnDhBlSpVtJ2CyEtatmxJVFQUy5Ytw8XFBYBHjx5Ro0YNxo8fT506dQDYu3cvfn5+RERE4OTkhKOjIzY2Nqxbtw57e3utPpZUJyYmhjVr1rB27VpKlizJqFGjzLVlbG1tzUFO/VrepPigtX37dmbPnk2VKlXMxebjV01GRkYya9YsBgwYoHmNiFgNZT2RpKesJ2mVsp5YImU9SUt0M84K3Lx5k9atWzN//nyKFy8OwNWrVxk3bhzff/89S5cupUKFCokG15cHVj12LvKn1q1bExcXx6JFi3BxcTHX43jw4AFdunRh9OjRlCpVyjxhOH36NFevXuX69evky5ePunXrYmtrq+NKUp34Pv3s2TMCAwPZsWMH2bNnx9fXFzc3t0SvVf+WlBAWFsaiRYvYt28f5cuXf23hblD/FBHroawnkrSU9SStUtYTS6esJ2mBbsZZiZEjR5ItWza++uor8wnp8uXLDBs2jJCQEAICAsibN28Kt1LE8gUGBjJhwgSWL19O+fLlzeEMwMfHhw0bNuDn54fBYCBLliwULVoUR0fHV1bmqIC3WKrXXaRLuL1D/J8jIyPZv38/ixcv5o8//qBr166ULVuWUqVKpUSzRcx98/Hjx6xevZpNmzaROXNmxo4dS44cOUifPr35NVqpLiLWRFlPJGko64m1U9aT1EpZT9IK3YyzEi8Xuow/QcVvYxISEsLChQsV0kT+wR9//MGIESM4d+4cs2fPpkyZMgD06dOH7777jly5chEbG8vt27cByJYtGw4ODnh7e1OzZs0UbLnIP0s4ab1x4wZRUVHmGhgJJQxsRqMRf39/rl27xvfff0+NGjXIkycPX3311Rttu1i/hP3zr/b/T7ii9/z58/j5+RESEkKBAgX4/PPPyZYtm/nJERERa6GsJ5I0lPXEminriSVT1hN5QTfjrEi9evXIkycP/v7+iX5+7do1vL29uXDhArt27SJHjhwp1EIRy7VgwQKyZ89Oo0aNuH37NiNHjuTcuXMsW7aM2bNnc+nSJSZNmkSBAgWIiIggIiKCX3/9ld9++40HDx4wY8YMPSYvqYafnx9bt27l4cOHfPjhh3h7e+Ph4fGP77t06RKhoaHkypUrUW0akf8qYTjbvHkz169fx83NjebNm5tXrMd7ObwdOHCAixcvcuTIETJnzsywYcPIkiXLG22/iEhyU9YT+b9T1pO0RFlPLI2ynsifdDPOCvxdocv43126dImlS5cycuRIbacg8hp+fn5kzZqVtm3bAvD7778zfPhwvv/+e3LlysWaNWvImjUr8Nf7U2vfarFUCSe/K1asYObMmQwYMACTycS8efPInTs348ePf21Iix9H/mr1msh/lbBvTZo0idWrV5M3b17Onz9PjRo1GD58+GsvLr+8RdTz58+xsbF5JdCJiKRmynoi/52ynlgzZT2xZMp6IonpZpwV+beFLrW/ucirvvvuO+bPn8+UKVPMk9Rbt24xffp0Dh06xLJlyyhSpEii98RPeuNPo5q8iqU7evQoN27cwNXVlXr16gEvVkB27tyZPHny/GVIE3kT7ty5Q7du3Rg3bhx58+blypUrdO3alfLlyzNixAg97SEiaZqynsj/nbKepAXKemLJlPVEXlC1QythMpnIkCEDHTp0oG7duhw9epQWLVpw+fJlwsPDza8BTSJFXidfvnyYTCYuX74MvDhePDw86N+/PyVLlqRjx46cPn060XviV58ZDAYdV2Lxrly5QseOHRk5ciRhYWHmnxcuXJiFCxdy69Ythg0bxrVr11KwlZJWzZ8/n1GjRlGgQAHefvtt0qdPT5kyZZg7dy7Hjh1j9OjR3Lt3L6WbKSKSIpT1RP4bZT2xdsp6YsmU9UT+pJtxqYTRaDT/+XUPM8Y/Vp45c2bat2/PhAkTsLe3p0+fPgwZMoSDBw9y7tw54M9JpYj8qUCBAhQoUIDx48cTHR1tPqZy5crFmDFjKF68ON26dePEiRMp3VSRf+XlscLDwwM/Pz+yZMnCjz/+SHR0tPl18SHt2LFjLFu2LCWaK2lYbGwsTk5O/PDDD1y4cIGYmBjgRd8sV64c8+bN4/jx4/Tv35+QkJAUbq2ISNJT1hNJXsp6Ym2U9SS1UNYTSUzbVKYCKnQpkrzij7Fbt27x9ddfU7BgQSZPnoy9vb35mPrjjz/o1asXWbNmZf78+SndZJG/lXDciIiIMK/odXZ2Zvv27QwdOpQ6deowbty4RDUCbt++zVtvvaXtrSRZJeyf8eLi4tiwYQOjRo2idevWr9RD+vHHH1mwYAEBAQG60CwiVkVZTyR5KeuJtVHWE0umrCfy93QzzsKp0KXImxMTE8OaNWtYu3YtJUuWZNSoUYmKdD948IAsWbJociAWLeHkd8GCBRw7dozLly/j7u5Ox44dqVGjBtu3b2fIkCHUr1+fMWPGvLL1jurNSHJJ2D+PHTvGvXv3sLW1pUSJEuTOnZtVq1YxduxYOnTogKenJ/DqxefXBTwRkdRIWU/kzVHWE2ugrCeWTFlP5J/Z/fNLJCXFn5Du3LnDkSNHWLZsWaJCl6NGjXptocuXB9Z06dK9sTaLpEYmkwl7e3uaNGlCeHg4O3bs4KuvvsLX1xc3NzcAsmXLBrwIcvb29inZXJG/FD9x9fPzY/Xq1fTu3ZtSpUpx6dIlvv76ayZMmEDjxo0B8PHxISwsjJkzZyb6DIUzSS7x/dPX15edO3cCL7Yuefr0Kb6+vrRs2RKTycT48eOxsbFhwIABr1xAUDgTEWuhrCfyZijribVQ1hNLpqwn8s90My4VmD9/Pr/++qu50KWDg4O50GX37t0ZPXr0X66aFJE/vW6FTfwqnPjtG5ydnenQoQN58+Zl8eLF1KtXj65du1K2bFlKlSoFoHAmFufhw4dkzZrV/PcrV64QHBzM9OnTqVSpEgAhISG4u7szdOhQ8ubNS926dYmKimLz5s1afSZv1Jo1a9i8eTPTp0+nUKFC3Llzh8DAQHr37s3ixYtp1aoVNjY2jBw5krfeeotWrVqldJNFRJKNsp5I0lDWE2ulrCepibKeyN/T2djCqdClSNJIOAG9ceMGFy9eBEi0Cic+pDk5OVGnTh3Wrl1Lq1atOHXqFF27dmXo0KGqISAW56uvvmLWrFmJfhYWFsbdu3fJkCGD+Wdubm60bduWokWLsm/fPgDq169PYGAgNjY2GI3GN9puSRtmzJjB48ePgRdzF5PJxG+//Ubjxo0pX748mTJlolixYvTr148qVaowZswYwsLCaNKkCbNnz+aLL75I4W8gIpJ8lPVEkoaynlgrZT2xZMp6Iv873YyzMC8PkHZ2drRu3ZqhQ4dy8+ZN8+Pl8RPJsmXLMmPGDNKlS0emTJlSoMUiqUPC7Rw6duzI559/To8ePbh161ai1yUMbDY2NvTs2ZOpU6eybNkyGjduTIMGDd5ou0X+iZeXF0OHDgUgPDwcgKioKGJjYwkLCwP+HFvc3d1xcnIiMjISSLzyV6slJamdPn2aI0eOkD59egDzyvSbN2/y5MmTRK/NkSMH1apV4/79+4SFheHg4EDNmjWxs7MjNjY2BVovIpL0lPVEkoeynlgrZT2xVMp6Iv832qbSgvxdoctmzZoRGxvL2LFjsbOzw9PT0xzSKlasSMWKFV/5DBFJfEysWLGC1atXM2DAAEwmE/PmzWPIkCGMHz8eDw+PV94bv62JyWSicOHCb7rpIv9KwYIFAViyZAnbt29n9uzZvP/++xQpUoQxY8Ywf/58c/+OiIjAZDKRP3/+lGyypBElSpRg9erVGAwG9u7dS6lSpciRIwe5c+fmhx9+4M6dO7z11lvm18f/7uXtoezsNF0VkdRPWU8k6SnribVT1hNLpawn8n9jMJlMppRuhCT2V4Uuq1evzsqVKxk/fjwdO3ZkwIABKdxSkdTj6NGj3LhxA1dXV+rVqwfApUuX6Ny5M3ny5PnLkCZiqeIvIMQ7efIknTt3pkSJEkyaNInw8HAGDBhASEgIrVq1wtnZmf379/Pw4UM2bNigSa+8Mbdv36ZmzZrUrFmTyZMnExkZSYsWLciePTujR48ma9asGAwG+vXrh4ODA/7+/q8U8hYRsRbKeiJJT1lPrI2ynqQWynoi/xvdjLMwa9asYdasWa8Uuty2bRuLFy+mQoUKrF69mpEjRzJ8+HAVuhT5F65cuULdunUBXjluLl26RJcuXcibNy8jR47UKjJJFV5eGR8ZGYmTkxNnz56lc+fOFCtWjNGjR+Po6Mj48eM5c+YM6dOnJ1++fEyYMAF7e3vi4uKwtbVNwW8h1up1T24cPnyYfv36UblyZXx8fLh9+zaDBg0iLCyM9OnT4+rqSlxcHN9++y329vZ6+kNErJKynkjSU9YTa6OsJ5ZMWU/kv9HNuBQ0Y8YM2rVrR+bMmYn/Zxg6dChZsmRJtBLy3r17jBo1ilu3brFixQrSpUtHcHAwH3/8sVa7iLzGy6vIoqOj2bdvH2PHjqV8+fL4+vri4OBgft3ly5dp2LAhzZs3Z/jw4SnYcpF/9vJ2PMePH+fx48f4+PhQoEABzp49S6dOnShatChTpkwhS5YsPHnyBHt7e5ydnTEYDMTGxmr8kGSRsH+eP3+eyMhIMmXKRP78+Tl69Cg9evSgevXq+Pj44OzszKpVq4iKiiJLliw0atQIW1tb9U8RsQrKeiLJQ1lPrJmynlgyZT2R/063oVOICl2KJA+j0WgOZxERETx9+pTY2Fhq167NkCFDOHjwICNHjkxUI6BQoULs3r3bXBhZxJLFT34nT56Mv78/rq6uVK5cmRw5cgBQvHhxFi1axKVLlxg4cCC3bt0iU6ZMuLi4mPu8Jr+SHEwmk7l/+vn58fXXX9OrVy927dpFXFwclSpVYvbs2Xz33XcMHz6c6Oho2rdvT9euXWnatCm2trbExcWpf4pIqqesJ5I8lPXE2inriaVS1hNJGjoCUogKXYokvYSrdBYsWMCxY8e4fPky7u7udOzY0bx9yZAhQ7CxsWHMmDHmMJc7d24AbecgqUJwcDA7d+4kICCA4sWLc/fuXX755Re2bNnCu+++S6tWrViwYAFNmjRh2bJlDBkyxPxe7c8uySW+b82ZM4d169Yxffp0XFxc8PDwIDY2lrt37/LBBx8wd+5cevbsSa9evZg2bZr5qRGDwaDzr4hYBWU9kaSnrCdphbKeWCJlPZGkoSfjUpDBYOD27dv06tWLMWPG8OzZMzw9PQEYOHAgV65cITQ0lLCwMAIDA8mePTvZs2dP4VaLWK6Eq3QWLVpE1apVadKkCVmyZOHrr79m48aN1K1bl/Hjx7Njxw769OnzymdociCpwdOnTylYsKB5O4iRI0cyYsQILl26xOjRo1m3bh3Fixdn165dDBo0KKWbK2lIREQEv/76K0OGDKFChQo4ODiwfPlyateuTe3atfnmm294//33mTJlCgAZM2YEdOFARKyPsp5I0lLWk7RCWU8slbKeyH+npXZv2MtFKnPnzs3ChQvp168f3t7e+Pj44Ovry6BBg2jTps0rhS4NBoMKXYok8PDhQ7JmzWr++5UrVwgODmb69OlUqlQJgJCQENzd3Rk6dCh58+albt26REVFsXnzZh1PYvFe10czZszI4cOH6dixIydOnKBevXoMHDiQOnXq0KlTJ65duwZAvnz5AK0CljcnKiqKK1eucObMGZ48ecKSJUvImTMn9erVw2QyMW3aNOrUqcPHH3/Mxx9/DLy+j4uIpEbKeiJJS1lPrJ2ynqQmynoi/51uxr1Bf1Xo8sMPP2TmzJn06NGDCRMm4OPjw9atW1XoUuQffPXVV+TMmZNRo0aZfxYWFsbdu3fJkCGD+Wdubm60bduWH3/8kX379lG2bFnq169PkyZNAE0OxHIl7Jtnzpzh7t27FCtWjMqVKzNnzhxOnjxJjx49qFKlivk9oaGhr6ysVziT5PDyudNoNJIlSxZatmzJ4sWLMZlMtGjRgho1alCqVCmCg4M5fvw4Tk5OiT5H518RsQbKeiJJS1lPrJ2ynlgyZT2R5KGZ/hvycqHLbdu2ERUVRevWrenatau50GXPnj2JiYlh/PjxtG/fPtFnqNClSGJeXl54eHgAEB4eTvr06YmKiiI2NpawsDDgzwmEu7s7Tk5OREZGAiSqyaHJgViihOPGlClT2L59O8+ePaNx48YMGDCAGjVqUKNGDa5evUpwcDAAK1asICoqijZt2qRk0yUNSBjOVqxYwenTp7l9+zZz5syha9eufPbZZ2TOnNl8scxkMrF06VLSp09P+vTpU7LpIiJJTllPJOkp64k1U9YTS6asJ5J8NNt/Q1ToUiTpFSxYEIAlS5awfft2Zs+ezfvvv0+RIkUYM2YM8+fPNwe4iIgITCYT+fPnT8kmi/xr8eNGQEAAmzZtYurUqeTLlw8nJyeePXvGkydPSJ8+PVeuXKF///4UKFCA7Nmzs2HDBuzs7LRdiSSr+HA2adIkNmzYQK1atShXrhwmkwmAvHnzcu/ePYYMGUJcXBwPHz4kOjpa27CJiFVS1hNJesp6Ys2U9cSSKeuJJB+DKf5IkmQXERFB3759adSoEfXq1ePSpUvs3buXb7/9locPH9KvXz86duzIgQMHCAwMZNGiRTp5ibxG/EWLeCdPnqRz586UKFGCSZMmER4ezoABAwgJCaFVq1Y4Ozuzf/9+Hj58aJ68iqQGkZGR9O3blypVqtC6dWvOnj3L7t27Wb9+PREREbRu3RpPT0+uXLlChgwZyJo1KwaDQdtcyRsRFBTE+PHjCQgIoGDBgjx+/JhLly6xc+dOypUrR5kyZThw4ABnzpwhb968dO7cGTs7O/VPEbFKynoiSUNZT9IKZT2xZMp6IslDN+PeoEePHvH5559Tq1YtcuXKZS50WbZsWUwmE0uWLCEoKIgcOXKY36PVBCKJvXxMREZG4uTkxNmzZ+ncuTPFihVj9OjRODo6Mn78eM6cOUP69OnJly8fEyZMwN7eXqvIJFUwmUw8f/6cnj174ubmRsGCBVmzZg0eHh5UrVqVyMhI5s2bx65du8idO7f5fRo35E3ZuXMn69evZ8aMGZw7d45vvvmG06dPYzKZCA8PZ/LkyXzyySeJ3qPzr4hYK2U9kf9OWU/SCmU9sXTKeiLJQ7eqk4kKXYokvZf3rT5+/DiPHz/Gx8eH4sWLs3DhQjp16sSwYcOYMmUK06ZN48mTJ9jb2+Ps7KxVZGLRXh43DAYDTk5OfPjhh2zatIng4GDatm1LzZo1KVq0KJcvXyY4OJiX19Ro3JDk8PIqdYCoqChOnz5Np06dOHHiBHXr1mXQoEHUqVOHJk2acPLkyVcCmsKZiFgDZT2RpKesJ9ZMWU8smbKeyJujJ+OSwd8VusyQIQM3btx4pdBlly5dsLW1Zd68ea+cAEUkscmTJ7N582Zq1KiBh4cHrVq1wsXFBYCzZ8/StWtXChcuzOjRo811BOD1EwwRS5Bw3Ni9ezf37t3j6tWr1K9fnzJlyhATE4PJZDLXEEiXLh1dunTBZDKxaNEi9WtJVgn757NnzwgPDzc/2bF582auXr3Ku+++S6VKlXB0dCQmJoZ27drRoEEDWrZsmZJNFxFJcsp6IslLWU+sjbKeWDJlPZE3SzfjklHCQpeZM2emY8eOZMyYEYB79+4xZsyYVwpd2tvb67Fzkb8RHBzMiBEjmDNnDsWLF+fu3btcunSJLVu28O6779KqVSvOnj1LkyZNaNeuHUOGDEnpJov8a76+vuzYsYOSJUty//59Lly4QNOmTfHy8uLRo0dMmzaNO3fu8Pz5c2JjY1m3bp3GDUlWCS9sLViwgMOHD3PhwgUKFChAtWrVaN++PY6Ojty+fZubN29iMplYtmwZv//+Oxs3btTqdBGxWsp6IklPWU+smbKeWBplPZE3T0dNMgkKCmL37t2sXLnSXOjywoULiQpdvv/++5w5c4bSpUur0KXIv/T06VMKFixI/vz5OXr0KIGBgVy8eJEMGTKwdetW7O3tadasGbt27Uq0UlLE0m3dupXNmzcTEBBAsWLFOHr0KJ07d6Z69eo8fPgQd3d3SpcuTbZs2ciSJQvt27fXuCHJLj6czZgxg3Xr1tGvXz/Kli1L7969WbFiBdWqVaNQoUIcOnSI2bNnkzFjRnLlysWGDRuws7NT3QARsUrKeiLJQ1lPrJWynlgiZT2RN09n9GQSExNDgQIFyJkzJ8eOHUtU6HLTpk1MnjyZNm3aJHpPXFycBlmRBF63AixjxowcPnyYjh07cuLECerVq8fAgQOpU6cOnTp14tq1awDky5cPUAFZsVwv9+/bt29TsWJFihUrxrZt2xg+fDhDhgwhZ86cjBw5kpEjR2rckDfOZDJx+/Zt9u3bx9ixY/n44485duwYt2/fZsKECYSGhvLrr7/SsmVLSpQoQZYsWciZMyc2Nja6eCAiVktZT+S/U9YTa6asJ6mBsp7Im6fnnJPA63b6TFjosk2bNqRLl45BgwYRHBxM/vz5OXny5Cvv0SRS5E8JJ69nzpxh3759/PHHH1SuXJk5c+ZQsWJFFixYwJQpU6hTpw4AoaGhZM+ePdHn6LgSSxXfvw8cOADArVu3iImJ4eTJkwwfPpyBAwfSunVr3NzcOHLkCD///PMrn6H+LcnBaDSa/2wwGDAYDERERPDxxx/z3Xff0aVLFwYOHEitWrVYtmwZAQEBAJQsWRJ3d3dsbGwwGo0KZyJiFZT1RJKesp5YO2U9sVTKeiIpS0fOf/RXhS4bNWqEwWDg6tWrdOvWLVGhS0dHR9zd3VO45SKWy2QymY+rKVOmsH37dp49e0bjxo0ZMGAANWrUoEaNGly9epXg4GAAVqxYQVRU1CuryUQsTcJxY86cOSxZsoT169dTt25d+vTpw549e5gwYQKNGzcGICQkBA8PD23FI29EwvPv1KlTcXNzo3HjxkRGRuLt7c2ePXsYNGgQLVq0AMDNzY27d+++8jmqayEi1kBZTyTpKeuJNVPWE0umrCeS8nQz7j9IeBL7p0KXx48fNxe6jIiIoFmzZincehHLFb9vdUBAAJs2bWLq1Knky5cPJycnnj17xpMnT0ifPj1Xrlyhf//+FChQgOzZs2vfakkV4seNPXv2EBYWhr+/P3ny5CFdunTUqlWLI0eO8PDhQ8LCwrhz5w4zZswgY8aMlC5dOoVbLmlB/Pn3l19+Ydu2bUyYMAEnJycaNmzI2rVrqVmzpjmcmUwmzp8/T6lSpVKyySIiyUJZTyR5KOuJNVPWE0umrCeS8nQz7j9QoUuR5BMZGcmxY8fo3r07FStW5OzZs+zevZv169cTERFB69at8fT0ZNOmTWTIkIGsWbNiMBi0b7VYLJPJZB43rly5Qu/evYEX2z0AZM+enQ4dOpAuXTrmz5/PnDlzyJEjB1myZGHZsmXY2tpq3JA3YsGCBezatYtq1arx/vvvA9CgQQPu3LnDkSNHGDZsGJkyZeK3334jIiICT0/PFG6xiEjSU9YTST7KemJtlPUktVDWE0lZBtPrNsGXfyW+0OXXX39N//79zYUuu3TpwoQJE8iaNSs2NjaULVuWU6dOqdClyL9kMpl4/vw5PXv2xM3NjYIFC7JmzRo8PDyoWrUqkZGRzJs3j127dpE7d27z+15XBFzEEiQMZ/fu3SNHjhzs2rWLsWPH8u677zJp0iScnZ0BiIiI4MmTJ5w9e5acOXNSokQJjRuSrBL2T4Dly5czdepU8ubNS2BgIBkzZgTg0qVLBAcH8+2335IrVy7c3d0ZPny4LjqLiFVS1hNJHsp6Ym2U9cSSKeuJWBad6f9HCSeAryt0OWDAAHOhyz59+hAdHc3cuXPNq2HiP0ODrMifXg5WBoMBJycnPvzwQzZt2kRwcDBt27alZs2aFC1alMuXLxMcHMzLawkUzsQSJezf33//PZMmTWLy5MnUqlULk8nEkCFDGD16NOPHj8fGxgYXFxdcXV0TXXyIi4vTuCHJImE427ZtG0WKFKFNmzY4OTkxYsQIZs6ciY+PDwCFCxemcOHCtGvXDnt7e/Nn6OKBiFgLZT2RpKesJ9ZMWU8smbKeiOXR0fQ/UKFLkaSXcPK6e/du7t27x9WrV6lfvz7t2rWjZcuWmEwmcw0Bo9HIhAkTXpnAiliihP1769at7N+/n4sXLzJu3Di8vb2pXbs2AN7e3hgMBsaNG/faMUKr0CQ5JOyfv/32G8uWLcPFxYXRo0fTtGlTYmNjGT16NA4ODgwaNMj8noRhzGQyKZyJiFVQ1hNJesp6Ys2U9cSSKeuJWCYdUf8DFboUSXrxkwNfX1927NhByZIluX//Pps3b6Zp06Z4eXnx6NEjhg8fzp07d3j+/DmxsbGsW7cOg8Gg7UrEosX3zUmTJrFt2zbq1atHgwYNOHPmDOPHj8fLy8sc0oYOHUpoaChz5sxJtI2ESHJIeNF51qxZ/PTTT9y9e5f79+8zYsQIhg4dSvPmzQEYM2YMBoMBLy+vV8636qsiYi2U9USSnrKeWDNlPbFUynoilks34/5HKnQpkvS2bt3K5s2bCQgIoFixYhw9epTOnTtTvXp1Hj58iLu7O6VLlyZbtmxkyZKF9u3bY2dnp8flJVU4deoU+/btw8/Pj/LlywMQHBzMunXrmDRpEj4+PtSuXZuoqCg2btz4yp7uIskhvo8FBgaydOlSpkyZQt68eTly5AhBQUGMGzcOHx8fmjdvjsFgYPjw4bi7u9OmTZsUbrmISPJR1hNJesp6Ys2U9cQSKeuJWC7NbP7BywOls7Mz165dw2g0EhoaSsaMGSlevDg9e/ZMVOgyf/78KnQp8hdeXuF4+/ZtKlasSLFixdi2bRvDhw9nyJAh5MyZk5EjRzJy5MhXJgXaV11Si5iYGMLDw3F1dTX/rEqVKsTGxuLt7c3o0aPx8fGhUaNGNGjQABsbG60ClmRnMpmIi4vj2LFjtG7dmqpVqwKQL18+smfPzty5cxk7diwjR47kiy++wM3NzfwaERFroawnkvSU9SQtUdYTS6SsJ2K5dPb/Gy8Xurx06RJt2rRh2LBhXL58mZkzZ5pfW7hwYTp16sSWLVtYuHAho0ePNq/mUjgTSSx+4nngwAEAbt26RUxMDCdPnmT48OEMHDiQ1q1b4+bmxpEjR/j5559f+QwdV2KJ4gvNm0wmjEYj8CKgGQwGHj9+DLy4uABQvXp13N3duX//PlOmTOHKlSvY2Ngk2lJCJLkYDAbs7OyIiIggNDQU+LP/1qxZkwoVKnD48GHGjBnD9evXqVmzJvb29sTGxqZks0VEkoyynkjyUNYTa6WsJ6mFsp6I5dII8BeMRqM5nMUXupwwYQK3b9+madOm+Pj4sHr1aiZNmpToPSp0KfLX4iesAHPmzMHT05ObN29St25djhw5whdffIGPjw+tWrUCICQkBA8PDzw8PFKqySL/WsJxw2g08uzZMwAqVqxIyZIlGTFiBNevXzdfXAgJCSFr1qzUrVuXJ0+ecPz4cUD7skvySHj+TcjDw4NDhw5x586dRH0vf/78vPPOO0RFRfHNN98QGRkJoHmNiFgFZT2RpKesJ9ZMWU8smbKeSOqhm3Gv8XKhyylTpnD37l2OHj3KiBEjuHr1Ks2bN2f48OEsW7aMyZMnAy9WgCU8uWmQFUks/rjas2cPYWFh+Pv7kydPHgoXLkytWrVwd3fn4cOHhIWFceHCBaZMmULGjBkpXbp0Crdc5O8l3GpkyZIl9OjRg3r16tG5c2f27t2Ll5cXmTJlol27dgQEBLBmzRr69+9PeHg4/fr1I1OmTPz4448p/C3EWiXsn8eOHePgwYNs2rSJqKgo+vfvj5OTE/369ePy5cuEhYXx/PlzgoKCqFatGh9++CEHDhwgPDw8hb+FiEjSUNYTSR7KemKtlPXEkinriaQuBlP8c6ryisDAQGbPnv1KoUuDwYCPjw/58uVj7dq1DB8+nGHDhqnQpchfSLgN0JUrV6hbty4AU6ZMoV69egBcvnyZ1atXs2nTJmJjY8mRIwdZsmQhMDAQe3t71eOQVGHatGls3LiRTp06UapUKbp37467uzuzZs0iY8aMTJgwgfPnzxMbG0u+fPnw9fXF0dGRfv368fbbb9O9e/eU/gpixaZNm8bu3btxcnLizp07ZM6cmZ49e1KwYEG8vLx4/Pgx6dOnx8HBgefPn7N7926uXr1Kr169mD9/Prlz507pryAikmSU9USShrKepBXKemLJlPVEUgc9f/oaKnQpknQShrN79+5RsGBBpk+fztixY9m9ezfVq1fH2dmZQoUK0bdvXzp06MDZs2fJmTMnJUqUwMbGhtjYWD0uLxbv8uXL7Nmzh8mTJ1OpUiWOHz9OVFQU3bp14969e9jY2DB+/HiePn3K8+fPsbOz4+nTp8yfP58jR47Qq1evlP4KYsWWLVvGunXrmD9/PqVKlWLjxo14e3uTK1cuChQowJYtW1i7di1RUVE4ODjQrFkzANasWYOrqysZM2ZM4W8gIpI0lPVEko6ynqQVynpiyZT1RFIPbVP5Gip0KZI0Eu6r/v3339OlSxfOnz9PrVq1GDp0KIcPH2b06NHm/a1dXFzInTs3n376KaVKlcLGxoa4uDiFM7E4oaGhREZGkvDh8vDwcIxGI5UqVSIoKIjOnTvj6enJZ599hr+/P/PmzQNe9PM//viDbt260aZNG7Zv384333xDgQIFUurriBWLP79evHiRNm3aUKpUKXbs2MG4ceMYOXIkABMnTsRgMNC8eXPatWtHgQIFWLZsGd7e3mzYsIFRo0aRPn36FPwWIiJJR1lPJGko64m1UtaT1EJZTyT10c04VOhSJDkk3Ld669atrF+/nosXLzJu3DjOnj1L7dq1GT9+PLt27WLo0KGJwlxC2q5ELM2YMWPo1q0bjRs3Zu7cufzxxx8AZMiQgefPnzN58mQGDRrEoEGDaN26NQDp0qUjKirK/BklS5akXbt2jBs3jqVLl1K8ePEU+S5ifQ4dOsSmTZs4d+4cERER2NjYEBUVxYkTJ3BxceHkyZMMHTqUAQMG0KJFC+Li4li1ahWnTp0yf8b333/Pnj17ePbsGStXrqRo0aIp+I1ERP4bZT2RpKesJ9ZKWU8smbKeSOqX5hPFy4Uunz59yuPHj6lduzb9+/fn119/pV+/fowdO5bs2bPj4OBgLnSZLl06li1bxtdff42Tk1MKfxMRyxJ/XE2aNIlt27ZRr149GjRowJkzZxg/fjxeXl7Url0bgKFDhxIaGsqcOXNeG9JELEWbNm0IDQ2lcuXKXL16lblz52JjY0PXrl3JnDkzpUuXZvny5TRr1owWLVoAL8aZBw8eUKxYMQBzTYz4/i+SVLp37865c+e4e/cuzs7ONG/enB49epA+fXpq167NkiVLmDJlCqNHj6ZJkyYAPHv2jAIFCpA9e3bz5/Tr1w+AmJgY7O3tU+S7iIgkBWU9keShrCfWSFlPLJmynoh1SPM34+InkS8Xupw3bx49e/Zk8uTJeHl50aFDh0SFLhcsWMDVq1fZuHEj0dHRKfwtRCzTqVOn2LdvH35+fpQvXx6A4OBg1q1bx6RJk/Dx8aF27dpERUWxcePGRDUHRCxNy5YtiYqKYtWqVbi6ugLQq1cvNmzYQIcOHXBzc6N169bcu3ePn3/+menTp5M5c2a+++47IiMj6datG6AVwJI8WrZsSWxsLNOmTcPd3Z3Zs2ezfv16GjVqRJEiRShbtix79+4lU6ZM5M+fH4BHjx6xatUq3N3dyZYtG5D4wrXCmYikdsp6IslHWU+sibKeWDJlPRHrkeZvxoEKXYokl5iYGMLDw82TWYAqVaoQGxuLt7c3o0ePxsfHh0aNGtGgQQNsbGwSTQ5ELEWbNm2Ijo5m+fLlODs7ExkZiZOTExUqVODZs2fmPvv+++/Tr18/9u7dy5o1a8ifPz/u7u4sXLgQOzs780pJkaQUf/Fg2bJluLi4AODl5cWWLVs4d+4cRYoU4f3336dr164sXbqUzp07kzVrVuzt7bG3t2ft2rU6/4qI1VLWE0keynpiLZT1xJIp64lYlzR9My7+RPRPhS5HjBhB8+bNAfjpp59YtmwZFy5cICgoiGXLlqnQpQiYVzqaTCZMJhM2NjbExMRgMBh4/Pgx8OeWDdWrV8fd3Z379+8zZcoUhgwZQsGCBc3vE7Ek7du358aNG+zcuRNnZ2eio6PN21UdO3YMV1dXnj9/jo2NDXZ2dlSqVIlKlSrRr18/HB0dcXBwACA2Nlb1ZiTJtWvXjpiYGFatWoWjoyPR0dE4ODgQGxtL4cKF8fDwML+2du3aFChQgCtXrnDjxg08PDyoXbs2tra26p8iYnWU9USSjrKeWCtlPbFkynoi1idNHYmHDh3i0aNHFClSBA8PD1xdXc2FLps2bWoudOnl5UWLFi04duwYq1atokmTJpQsWRJ4Uejy559/Jlu2bKxcuZLChQun8LcSSXkJV9gYjUYiIyNxdXWlYsWKlCxZkhEjRrBgwQLy5csHQEhICFmzZqVKlSocPnyY48ePU7BgQW1bIhYnJiaGjBkz8vz5c06cOEH58uVJly4d8GI12u7du/Hw8KBVq1aYTCZy5cpF5cqVcXNzo1atWuZwZjKZNPmVJLdkyRJ++uknAgICcHR0JC4uztznpk2bxpkzZ7h79y67d+8mQ4YMlC1blvz581OkSJFEnxMXF6f+KSKpnrKeSPJQ1hNrpawnlkxZT8Q6GUwmkymlG/Em/F2hS39/f9auXcvDhw8TFboMDg5m4sSJfPPNN+TIkSPR56nQpcgLCcPZkiVLOHr0KBcuXKBQoUI0b96cAgUK4O3tzd27d2nbti0ZMmRg586dPH/+nNWrV9OpUycyZcrE1KlTU/ibiLxebGwsXl5eHDx4kJkzZ/LBBx/Qu3dvLl68SIsWLXB1deXu3bucPn2a27dvc/nyZUqWLMnatWt10UGSVXh4OH379uXKlSuMHz+eypUrA9CnTx+Cg4PJkSMHdnZ2XL58GYBMmTJhZ2fHiBEj+OSTT1Ky6SIiSUpZTyR5KOuJtVPWE0ulrCdindLErXEVuhRJPvHHxLRp09i4cSOdOnXiq6++onv37jx69IhZs2axaNEiJkyYwM6dO4mNjSVfvv/X3p1HVVXv/x9/HQ6TgEiOTI4lVipWWvenlqY3M9PrnAPidDWlnNAcMk2DnFEiUXGqECVHcE5Ts7S4mWFXMb0aqXkdEgfQlJjh94dfzgXFJjlyODwfa7VanL338bPX2ufsz+t8PvvzrqUlS5ZIklxdXfXII4+U5CkAv8nW1lZz5szR2LFjNXr0aNWuXVtpaWlasWJFoR/v8pftOXbsmB5//HHTUj6ENJhL+fLlNX/+fI0YMUITJ07UwoULtXTpUv30009atWqV6tSpo4yMDKWkpOjUqVM6cOCAUlJS1KpVq5JuOgAUG7IeYD5kPVg7sh4sFVkPsE5W/2RcUYUuf/nlFz377LMKDg5W586dJUk7duxQVFSUfvjhh7sKXdrZ2VHoEvgNP/74o4YPH66pU6eqadOmOnTokAYNGqTZs2ercuXK8vDwkKenp1JTU5Wenm4qbrxq1SpFR0dr9erVqlOnTkmfBvCbsrOzNXXqVMXExOjdd9/VK6+8YtqWm5srSYXuExTwxoOSmpqq4cOH6+uvv5aXl5ciIyNN9QPuVR+AugEArAFZDzA/sh7KArIeLBVZD7AuVv3JpNAlUPxu3Lghe3t7OTo6mmaB3bx5U7m5uWratKn27NmjcePGady4cWrbtq0GDRokLy8vBQcHy9nZWadPn9aMGTN048YN5eTk6KOPPiKcweIUFa7yl3xIT0/XnDlzVKlSJbVs2VJGo7HIH/AIZ3hQnJ2dFR4erkmTJumbb77RlStX5O3tLYPBYOq/3Dlzl34NgNKOrAcUP7IeygKyHkoTsh5gXaz2ybjIyEjNmjVLy5Yt03PPPVfoZjt58mRt2LBB8+bNk62tranQpcFgMBXDzMdsF+B/3n33XR0/flwpKSnq2LGjOnfuLE9PT506dUoDBw5Uhw4dtHbtWo0bN069evWSJA0bNkwuLi6aPXu26X127Nghd3d3eXp63lWjAygpx44d0/HjxwvNgixKdna2xo0bp7i4OM2ZM0ctWrRgNj0eiN97ciN/1uSPP/6o0NBQNWnShKVzAFglsh5Q/Mh6sGZkPVg6sh5QNljtYByFLoHi5e/vrxs3bqhZs2Y6ffq0Dhw4oGHDhmnIkCG6fv26pk6dqn379umVV17R22+/Lel2Z6JXr15q0aKFhg8fzg8esGj//ve/NWzYMA0YMEB5eXlq2rSpGjZsWGQHNzs7WxMmTND27dsVHR2txo0bl0CLUZYUnO14+PBh1apVS25ubnftl5qaqpEjR+rUqVOaPn26mjdv/oBbCgDmR9YDihdZD9aOrAdLRtYDyg6rHYyTbn9JjRgxQqdOnSpU6HLmzJn3LHQ5e/ZsHucF7pBfjyMqKkouLi6SpBEjRujkyZPasmWLHB0ddeDAAYWGhio9PV2tW7fWQw89pL179yo5OVkbN27kcwWLl5SUpA0bNujDDz9Uamqq9u3bp2rVqt1zhlpWVpYiIiL0+uuvc33DrApeg++//74+++wzLVmyRB4eHkXun5qaqr59+6patWqKiIh4kE0FgAeGrAcUD7IeygKyHiwVWQ8oW6x6ME6i0CVwv/z9/ZWWlqaVK1fKyclJaWlpKleunFauXKkvvvhCERERpiV/vv76a+3evVs7duxQ7dq15enpqZkzZ8rOzo6ZkigVIiMjNXfuXLm4uKh///567bXXJP3+khHcN/AgfPPNNwoPD9eQIUPUokWL39w3PT1d9vb2LKsDwKqR9YD7Q9ZDWULWgyUj6wFlg9XfTSh0Cfx1/fv319mzZ7Vjxw45OTkpMzNT5cqVkyTFx8fLxcVF6enpsrGxka2trZo2baqmTZtq9OjRcnBwMAU3Oq+wVHcGr0aNGmnlypWKi4tTdHS0MjIyFBgYKBsbm98MaVzfMLe4uDgFBQXp2rVrqlChgqTf/uHA0dHxd/cBgNKOrAf8dWQ9WDuyHkoLsh5QdljNJzY3N/ee21xcXDRjxgw99thjGjVqlOLj41XwgUAKXgJ3y8rKUoUKFZSenq7Dhw+bZt5I0vjx4/Xpp5/q+PHj8vPzU6dOnTRkyBBFRkZqy5YthcJZXl4enVdYpIId1/j4eG3btk1OTk568skn1b17d3Xr1k0bNmzQ+++/L0mysbFRTk5OSTYZZcidCxc0b95c7dq1U15enj744ANdvXpVNjY2d+13J8IZAGtA1gOKF1kP1o6sB0tG1gPKLqtYppJCl4B5ZGdna/z48dq3b5/mz5+v5s2ba+TIkfrhhx/Uq1cvubi46NKlS/r+++91/vx5/fjjj2rYsKHWrVvHDx+waAXvGyEhIdq2bZtycnLUpk0bTZw4Ufb29kpKStLHH3+s9evXq23btkpLS1OnTp3UtGnTEm49rF3BHw+uXLmi9PR007Jr7733nnbu3KmWLVsqICBAFStWvOupDwCwJmQ9wDzIerBWZD1YMrIeULaV+sE4Cl0C5pWdna2xY8fqX//6l2rXrq20tDQtW7ZM1apVM+2Tl5envLw8HTt2TI8//riMRiMdBpQKkZGRWr58ucLCwtSwYUOlp6crMzNTly5dUu3atU37bN26VXZ2dtq0aROzf2FWBfs1Cxcu1J49e3Tp0iV17txZEyZMkHT7R4UvvvhCzz77rIYOHUpIA2C1yHqAeZH1YM3IerA0ZD0ApX4wLh+FLgHzyc7O1tSpUxUTE6N3331Xr7zyimlb/rJBBT9PFPBGaZCVlaU33nhDvr6+Gjx4sI4ePart27dry5YtSktLU+vWrRUcHCw7OzulpqaqQoUKpuVLuL5hbnPnztX69es1aNAgGQwGzZs3T0OHDtXo0aNN2/ft26cGDRpo4sSJcnV1LeEWA4D5kPUA8yHrwRqR9WDJyHpA2WUVUz4odAkUn6I6n7a2tpo6darS09M1Z84cVapUSS1btpTRaCzyM0TnFaWB0WiUg4ODvvzyS928eVMxMTHy8fFRQECAjEajQkJCNHToUPn4+JjqYuTm5nJ9w+y+/vpr7dq1S8uWLZOvr6+++uorGQwGLVmyRL/88oumTp2qsWPH6tdff9WNGzfk4uJS0k0GALMh6wHFh6yHsoKsB0tF1gPKtlKZTih0CRSvY8eOaf369ZLuHa7s7e01e/ZsPfvss3rzzTf15ZdfmmZKApauqGvVxsZGzz//vIxGozZt2qT+/ftr8uTJ6tevn/7+97+rTp06dx3HfQMPwk8//aSKFSvK19dXJ06cUGRkpCZPnqy5c+dq9erVev/995WUlKQpU6Zo7ty5srGx4fsYgNUg6wHFi6wHa0fWQ2lC1gPKtlL3ZNy9Cl3mP8q7c+dOLV26lEKXwJ+QmZmp9957TykpKcrLy1PTpk3VsGHDuz47tra2CgkJ0YQJExQQEKDo6Gg1bty4hFoN/DEF7xubN2/WhQsXlJiYqDZt2uj5559X+/btlZWVJTs7OyUnJyszM1OTJk2Ss7OzfHx8Srj1sHZF9VPKly+vcuXKKSkpSVu3btXDDz+stm3bKjk5WZIUERGhlJQUvfPOOzIYDMrLy+PHAwBWgawHFD+yHqwZWQ+WjKwH4E6lajDu9wpdjh49WtnZ2friiy9kMBgodAn8QZ6enurTp4+WLFmi1NRUde7cWQaDocjlfWxtbTVr1izVrFlTjRo1KqEWA39c/jU8Z84cbd26Va1atVJ6errefvttNWvWTPPmzdP169c1f/58HTlyRHZ2dpKktWvXmmah0fmFORS8trKzs00zHjt06KDHHntM0u3l2UaPHq3KlSvr+vXrat++vfr27auGDRua3oc+DgBrQNYDzIOsB2tG1oOlIusBKEqpGozL/xIrqtClvb29Ro8erXHjxslgMGjfvn365ZdfKHQJ/AHVqlWTs7OzMjIy5ObmptjYWL322mv37Jza2dlp5MiRkm53KmxtS9VXCcqg3bt3a/v27Vq8eLHq16+vuLg4xcXFqVu3brp48aJq1aql5s2bq0aNGnJ1ddUrr7wio9HI9Q2zKfjdGhUVpe+//16JiYmqXbu2Xn31VT322GM6ePCgLly4oIceekjS7f5Pdna2GjVqJIPBQIF5AFaFrAeYB1kP1o6sB0tD1gNwL6XurkOhS6B43Bm8GjVqpJUrVyouLk7R0dHKyMhQYGDg784Wo/MKS3TnNXvp0iXVrVtX9evX1/bt2/X2229rwoQJqlu3roKCgjR8+HC1a9eu0Hvk5ORwfcNsCv7oHBsbq4CAADVs2FAffPCBBgwYoN27d6tatWpyd3fXsGHD5OLiInt7e23YsMG0XAnhDIC1IesBxYOsB2tG1oOlI+sBuJdSd+e5V6HLChUqaOzYsXJzc1OvXr00ZcoU05IlPHYOFFbwMxEfH2/qvNarV08eHh7KysoydQJGjRolGxsbZuWgVMm/vnfs2KE2bdooKSlJeXl5io+P19tvv62xY8fKz89Pt27d0rfffqujR4/K19e30HtwvcPcEhIS9Nlnn2nBggV66qmntH//fqWmpmrq1Kk6ffq0fHx8FBQUpJMnTyo9PV19+/aVra0ts3gBWC2yHnD/yHqwdmQ9lAZkPQBFsehPN4UugeJX8DMREhKibdu2KScnR23atNHEiRPl7u4uPz8/SbfXUb9+/brS0tLUqVMnNW3atCSbDvyugj8+REREKCIiQo899pg6dOig6Oho+fv7a+7cuerQoYMk6datW/L29lb16tVLstkoo1JTU5Wdna2nnnpKe/bs0bhx4zR27Fi98MILGjt2rOrVq6cRI0boqaeeMh3DLF4A1oKsBxQ/sh6sGVkPpQlZD0BRLPYTTqFLwDzyPxORkZHavHmzwsLC1LBhQ6Wnp+vGjRu6dOmSaR1rOzs7bd26VXZ2dpo2bVoJtxz4ffn3jZ07d+rq1atasmSJatWqpdTUVA0aNEirVq3SsWPH1LBhQ12/fl0RERFycHBQ8+bNS7jlsHZF/eickZEhR0dHRUdHa968eRo/frx69+6tvLw8Xb58WRUrVrzrfZjFC8AakPUA8yDrwZqR9WCpyHoA/iiLHIyj0CVgXllZWfruu+80YMAANWnSREePHtX27du1ZcsWpaWlqXXr1goODtaQIUPUp08fVahQgeVLUGokJSVpzJgxys3NVfXq1dW0aVM5Ozura9eucnR01LJly/Txxx/L3d1d1apV0+rVq2U0Grm+YTYF+zVJSUnKzs6Wl5eXWrRoodDQUL377ruaMGGCevfuLUlKT0+X0WhUzZo1S7LZAGAWZD3AvMh6sGZkPVgash6AP8OQl5eXV9KNuJeChS4NBoM++OADpaWlaffu3UpJSdHw4cN1/fr1QoUu7ezsipyRAOB/cnNzNWHCBF2+fFlPPPGEYmJi5OPjo+eff15Go1EhISFat26dfHx8Ch3DMkCwRPnf+QW/+xMSEjRq1Ch5enpq+vTpqlWrlqTbs+9v3rypEydOqFKlSnrkkUdkY2PDuux4IObPn6+dO3fq8uXL6tSpk8aOHavExESNGzdOzs7O6t69u8qVK6etW7fq6tWrio2N5boEYLXIeoB5kPVgTch6KC3IegD+CIsdjEtISNCECRM0ffp0U6HLN954Q1OnTpW3t7d8fHx04sQJCl0Cv+NewWr79u2KiYnRqVOn5O/vr7///e+qU6eOLl26pNdff10zZszQo48+WgItBv64gtf3tWvXTGGrSpUqOnz4sAICAuTr66ugoCB5eHj87nsAxSUvL0+5ubmmGbjLli3T8uXLNWTIEN26dUuRkZFq27atxo4dq19++UVTp07V+fPn5ebmppo1ayokJER2dnbM4gVglch6QPEg68GakfVgqch6AP4qix2M+/rrrzVlyhTt3r27UKHLbt26FSp0WRBfYkBhBTuemzdv1oULF5SYmKg2bdqoZcuWcnZ2VlZWluzs7JScnCwXFxe99tpryszM1IoVK+i0wqIVnB25aNEiffXVVzp//rwcHR01cOBA9e7dWwkJCXr11Vf15JNP6p133pG7u3sJtxplQXJycqEaAMePH9fBgwdVo0YNtW7dWpK0b98+jRw5Ui+++KKmTZsmBwcHXb58WXZ2dnJzc5PBYOBHZwBWi6wH3D+yHqwZWQ+WiqwH4H5YxKeeQpeAeeQHrDlz5mjr1q1q1aqV0tPT9fbbb6tZs2aaN2+erl+/rvnz5+vIkSOys7OTJK1du1Y2NjbMIoPFKnhthoeHKzo6WhMnTlR6erp+/PFHBQcH6+rVqxoxYoQWL16s119/XYGBgVq0aFGR9w+guEycOFHly5fXW2+9JUn67rvv5OfnZ1oWKl/Lli01f/58BQYGmo6rWrWqaXteXh7hDIBVIOsB5kHWg7Ui68FSkfUA3K8S73nl5uaawllSUpIuXLggSWrRooUMBoPeffddjRgxgkKXwF+0e/dubd++XYsXL1ZwcLD8/f2VlZWlbt266eLFi6pataqaN2+uf/zjH+rRo4fWr18vOzs7ZWdnE85gcT7++GNlZmaars2LFy8qLi5OM2fOVKdOndSzZ09NmjRJb775phYuXKg9e/boySef1Pz581W+fHm5ubmV7AnA6j377LMaN26cJCk1NVVPPfWU3nzzTdnZ2enYsWOF9s0PaVu3btXq1asLbaMeEgBrQNYDzIusB2tC1oOlI+sBuF8lPgyff5MtqtDltGnTNG7cOG3dulUODg6mQpepqanq379/CbccsEx3znC8dOmS6tatq/r162v79u16++23NWHCBNWtW1dBQUEaPny42rVrV+g9cnJymKUDi9OzZ0+5uLioR48eptdSU1P1ww8/yNHR0fRabm6uevXqpf3792vbtm1q0aKFnn76aT399NOm7fz4gOKW/+RH+/btJUnr16/Xtm3bNGfOHA0YMEBZWVmaN2+eypcvr4CAANNxzz33nNauXav69euXVNMBwGzIekDxIuvBWpH1YMnIegCKS4ncofLy8pSTk2P6e9myZYqOjla3bt3Ut29fxcbGKigoSJ6enoqIiJCzs7OWLVumqKgoubq6KiYmRra2toXeA8Bt+R3PHTt2KDs7W0lJScrLy1N8fLzefvttjR07Vn369FGFChX07bff6ujRo3e9B8sAwdL4+fkpKytL4eHhhX48yMvLk6urq86fP6/s7GxJtz8DDg4OcnZ2lr29vezt7Qu9F+EM5nDn7MYbN24oJSVF06dP1+XLl/Xqq69qzJgxCgsL05IlSwrt26hRI9na2pquYQAozch6gPmQ9WCNyHqwdGQ9AMXlgU+Hyi90md8BPH78uOzs7DRz5kxTocsnnnhCI0eOVE5OjqZNm6aVK1dS6BL4HQVngEVERCgiIkKPPfaYOnTooOjoaPn7+2vu3Lnq0KGDJOnWrVvy9vZW9erVS7LZwO/q3bu3MjIyFB0drXLlypkK0UuSj4+PHn30Uc2fP181atTQM888I4PBoLS0NF2/fl1/+9vfSrj1KAuKqoc0ePBglStXTjExMQoODtaUKVM0ZMgQSbefEElNTdWYMWMKHUO/BkBpR9YDzIOsB2tF1oOlI+sBKE4PdMrIxIkTtXjxYtPf3333nbp27aqQkBClp6ebXs9fV3fPnj2aPHmykpOTVbVqVT300EMyGAwUugSKkB/Odu7cqatXr2rJkiWqVauWqlevrkGDBsnNzU3Hjh3T2bNndeTIEb3zzjtycHBQ8+bNS7jlwL35+/tLUpHh7PPPP5ckvf/++6pZs6ZGjRqld955R+Hh4RoyZIhSUlI0dOjQEms7rN/x48clydQ3yZebmytJ6tOnj6lmS3BwsC5fvqwhQ4Zo0KBB+vbbbwsdAwClHVkPMB+yHqwRWQ+WjKwHwBwe6GAchS4B80pKStKYMWMUHR2tkydPSpKcnZ3VtWtXDR48WLGxserYsaPGjx+vX3/9VatXr5bRaGQZIFikiIgIxcfHq0+fPneFsxEjRigsLEw3b96Ug4ODVq1apQ4dOigxMVHffPONateurdjYWJa5gtlMnz5d48eP1/79+yUVDmk2NjaFQlrXrl118eJFTZs2TZcuXdLo0aP18ccf3xXsAKA0I+sB5kXWgzUh68GSkfUAmIsh7wF8M9z5SG/BQpfVqlXTsmXLNG/ePAUGBhYqdClJR44cUf369ZkdCRQh/7NV8DOWkJCgUaNGydPTU9OnT1etWrUkSdnZ2bp586ZOnDihSpUq6ZFHHpGNjQ3LAMFiHThwQCtWrNCVK1f0z3/+Uy+//LIkaeTIkTpz5owWL14sLy+vQsv2pKWlydbW1hTkuL5hLidPntTYsWP10EMPadCgQWrZsqWkwn2enJwc01Jta9as0YIFC9S1a1fTkiVFLXkCAKUNWQ8wD7IerBlZD5aMrAfAXB7IYNydli9fri1btqhWrVqaPHmyqlatqqVLlyo0NFSjR48u8lFzbrJAYQU7pdeuXTOFrSpVqujw4cMKCAiQr6+vgoKC5OHh8bvvAVii+Ph4LV++XFeuXFFgYKA2b96skydPatGiRYVqYBTV0aXzC3M7deqURo0apYceekiDBw++Z0i7ceOGKlasqK+++kpNmzY1hTYAsEZkPeD+kfVQFpD1YMnIegDMweyDcfe6QUZHRysmJkaenp6aMmWKKaTNnz9f//znP+8qdAngfwp+rhYtWqSvvvpK58+fl6OjowYOHKjevXsrISFBr776qp588km98847cnd3L+FWA39cwWs8P6QdOXJERqNRO3fulIuLCz8wwCLcK6TlO3nypEaOHKmXXnpJo0ePllR4FiUAlGZkPaD4kfVg7ch6KC3IegCKm9nubBS6BMwjNzfX1HENDw9XVFSUevbsqWHDhqlly5YKDg5WeHi4fH19tXjxYh05ckSBgYFKTk4u4ZYDf1zBe0eTJk306quvytfXVw899JAOHjwo6fZa7dwrUNIefvhhvf/++0pJSdHy5cu1b98+07YTJ07ozTfflL29vYYPH256nXAGoLQj6wHmQdZDWUDWQ2lB1gNQ3MzyZNz06dP19ddfa/z48WrRooWkwjNfCs5wWbVqlWJjY+Xt7a233npL7u7uRa6NDpR1H3/8sbp37y57e3tJ0sWLFzVmzBgNHTpUrVq1Mu23YsUKzZw5UwsWLNALL7ygb7/9VkuXLtWSJUuYWYZSp6hZk5cvX9Zrr72mNm3a3LUPUFLunDXp6empCRMmKCsrS7GxsbKzs2MZNgBWgawHFD+yHsoish5KC7IegOJilt5a9+7dZTAYCs0aKDjzxcbGRjk5OZIkf39/9ejRQ999950+/vjjQvtywwVu69mzpz777LNCASs1NVU//PCDHB0dTa/l5uaqV69eat68ubZt26bMzEw9/fTTWrZsmWxsbEyzlQFLc695IXfOmhw8eLCqVq2qJUuWaOvWraZ9gJKWP2vy+vXrCg8P1+DBg5WZmUk4A2B1yHpA8SLrwdqR9VDakfUAFBezDMbVq1dPYWFhSk5OvmdIMxqNysnJUXJysnr16qVZs2Zp1KhRpvfghgvc5ufnp6ysLIWHhxe6uefl5cnV1VXnz59Xdna2pNs/fjg4OMjZ2Vn29vammZX5mC0JS1RwOZ78vwv+v6hlTGxtbfWvf/3rwTcW+A0PP/ywwsLCdOnSJVWqVEmbNm0inAGwOmQ9oPiQ9WDtyHqwFmQ9AMXBLMtU5qPQJXB/evfurYyMDEVHR6tcuXLKysqSnZ2daXtAQICOHTumuXPn6plnnpHBYFBaWpqGDh2qv/3tbxo2bFgJth74fQVnxkdGRuro0aNyc3OTv7+/ateuXWipq4L7njhxQj4+PvzoAIt06dIlValSRUajkXAGwGqR9YD7Q9aDtSPrwRqR9QDcD7MOxkn3DmknTpzQxIkTlZ2dbXqsF8D/+Pv7KycnRx9++OFd4ezzzz9Xq1atlJGRoUGDBunHH39U27ZtVblyZR08eFDXr1/Xxo0b6RSg1FiwYIFWrlyphg0b6sKFC7K1tdW8efPk4+Nzz5AmFa5LA1gafnQGYO3IesBfQ9ZDWULWgzUi6wH4K8x+V8tfVzclJcW0jEliYqLeeuutQuEsf+kFAFJERITi4+PVp0+fu8LZiBEjFBYWpps3b8rBwUGrVq1Shw4dlJiYqG+++Ua1a9dWbGysbG1tTfU6AEtTsKZFbm6url+/roULF2r58uWaNGmSHnroIQUGBuqHH34oVAPjzmWtCGewZIQzANaOrAf8eWQ9WDuyHsoCsh6Av8LsT8blO3XqlAIDA+Xg4KArV66ofPny2rhxI+vrAkU4cOCAVqxYoStXruif//ynXn75ZUnSyJEjdebMGS1evFheXl6FZoqlpaXJ1tbWFOT4XMFSFbxud+/erbNnz2rdunUKCgpS06ZNJUn79u3TBx98oGvXriksLEx169a9a6YkAACwDGQ94I8j68GakfUAALi3BzYYJ90Oaf3791fVqlW1bt062dra0okE7iE+Pl7Lly/XlStXFBgYqM2bN+vkyZNatGiRqlevbtqvqE4rHVmUBiEhIVqxYoVq166txMREvfnmm+rVq5ccHR0lSfv379dHH32k48ePa8OGDYWuewAAYFnIesAfR9aDtSPrAQBwtweajB5++GFt2LCBQpfAb8gPV02aNJEkLV++XOPHj5fRaNTOnTvl4uJSaLZZUUGMcAZLl5CQoEOHDik6OlpVqlTR2rVrFRISIicnJ3Xs2FGOjo5q0aKFMjMzdeDAAXl6epZ0kwEAwG8g6wG/j6yHsoCsBwBA0R54OnJ3d5d0u9Al4Qy4m8FgKBTSDAaDli5dqosXL+rgwYNq3bq1bGxsmBGJUmv16tU6fvy43N3d1ahRI0nS6NGjlZmZqaCgIElSp06d5ODgoBdeeEEvvPCCJAokAwBg6ch6wG8j68HakfUAALi3EquGyk0WuLf8kCZJjRs31quvviovLy8tWLBAu3fvvmsfoDT55ZdftHHjRn333XdKTEw0vT5hwgQNGDBA06ZN0+rVq5WZmVnoOO4bAACUDtyzgXsj68GakfUAALi3EhuMA3DbvUJWwQDWpEkTDR48WFWrVtWSJUu0detW0z6AJcvNzb3rtaFDhyooKEgZGRlauXKlTp8+bdo2btw4de7cWXv27DEVqAcAAABKI7IerBlZDwCAP8eQx3QroMQUrAdQ8O+CrxdcouTQoUMKCQlR7dq1NXPmzBJpM/BHFbyOv/zyS127dk2XLl1Sx44d5enpqQ0bNig0NFRt27ZVv379VLt2bdOx+dc9S/QAAACgNCLrwZqR9QAA+PMYjANKSMGOZ2RkpI4ePSo3Nzf5+/urdu3a9wxpJ06ckI+PT6FgB1iykJAQbd++XeXLl9fVq1eVl5enESNGqE+fPlq3bp3mz5+vl156Sb169dIjjzxiOo5wBgAAgNKIrIeygqwHAMAfR1VtoITkdzwXLFiglStXqmHDhjp+/LgOHjyoefPmycfHxxTSCs4ae/TRRyXdPdMSsETr16/Xli1bFBERIW9vb7m6umrcuHEKDw+Xm5ubevTooYyMDE2fPl1eXl6FAhrhDAAAAKURWQ9lAVkPAIA/hyfjgAesYLDKzc3VjBkz9NJLL6lJkyb66quvtHTpUl29elVhYWGFQhpg6dasWaOnnnpKPj4+ptdmzZqlzMxMTZkyRVlZWabaAAEBATp9+rR27twpGxsbffrpp3rhhRco3A0AAIBSi6wHa0XWAwDg/tHrAx6ggmFr9+7d+vDDD7V//35lZWVJkp599lkNGjRIlStX1ujRo5WYmCgbG5t7Fv4GLEVcXJzeeecdRUdHm4p05+bm6tixYzp37pwkyc7OThkZGZKk1157TT///LOOHj0qSWrbtq2MRqNycnJK5gQAAACA+0DWg7Ui6wEAUDwYjAMeoPxwFhISotGjR2vz5s3673//q5MnTyo9PV2S1LJlSw0ePFhVq1aVv7+/zp07xxIOsHjNmzdXcHCwPvvsM61YscL048Jzzz2n8+fP6/PPP5ckOTg4SJJSU1NVq1Ytubu7F3ofZksCAACgNCLrwVqR9QAAKB7UjAMesISEBB06dEjR0dGqUqWK1q5dq5CQEDk5Oaljx45ydHRUixYtlJmZqQMHDsjT07Okmwz8pszMTNnb26tHjx66efOmoqKiZDAY9Nprr6ldu3baunWroqKilJ6ernbt2ikpKUlRUVHy8PBQ1apVS7r5AAAAQLEg68HakPUAACg+1IwDHqDVq1fr+PHjunnzpsLCwkyvz549W1FRUZo6dao6depkmlGWLycnh1lksEj5xeYlaeHChUpJSdGmTZt069YtdevWTePHj9fly5c1adIkXbhwQTk5OapSpYrs7Oy0du1a2dnZUSsDAAAApR5ZD9aGrAcAQPHiyTjgAfrll1+0ceNGVaxYUYmJiapbt64kacKECbKxsdG0adP066+/ys/PT/b29qbjCGewVPnhLDIyUpGRkXrvvffUqVMnHTlyRB999JHmzZunMWPGaPHixTpx4oROnjypGjVq6Pnnn5fRaFR2drZsbbkVAQAAoHQj68HakPUAAChePBkHmMm9ZoDFxMRozpw5atu2rQYMGKA6deqYtk2ZMkWnT5/WypUrqR2AUiF/tuSwYcNUq1YtjRs3zrRt06ZNCgkJUatWrTRkyBDVqFGj0LHMAgYAAEBpRNZDWUDWAwCgeDFFBTCDguHsyy+/1LVr13Tp0iV17NhR3bp1U15enkJDQ2U0GtWvXz/Vrl1bkhQcHGzq8BZcEgKwZJmZmbp27Zo8PDwkSVlZWbKzs1Pnzp118uRJrV69WpmZmRo2bJhq1qxpOo5wBgAAgNKGrIeyhKwHAEDxYTAOMIP8cBYSEqLt27erfPnyunr1qiIjIzVixAj16dNHubm5mj9/voxGo3r16qVHHnlEkghnsGh3zgI2GAyyt7dXo0aNtHHjRg0cOFBeXl6m/SpVqiQPDw85OTmpevXqJdhyAAAA4P6R9WCtyHoAAJgXg3GAmaxfv15btmxRRESEvL295erqqnHjxik8PFxubm7q0aOHMjIyNH36dHl5eZkCmiTCGSxSwXAWExOjs2fPysbGRoGBgRo2bJi+++479e3bV4sWLVK1atXk6OiogwcPqmfPnurfv78MBgMFvAEAAFDqkfVgbch6AACYHzXjgGKwZs0aPfXUU/Lx8TG9NmvWLGVmZmrKlCmmpRwkKSAgQKdPn9bOnTtlY2OjTz/9VC+88ALLOMCiFZzBO2vWLK1du1a1atXS6dOn1aBBAy1cuFAXL17UrFmzdOTIEVNAy8nJ0ebNm2Vra0s4AwAAQKlD1oO1I+sBAPBgMBgH3Ke4uDgNGjTINCOsTp06ys3NVf/+/eXo6Khly5ZJkjIyMuTg4KAjR47I399fq1atUqNGjUzvQ4FjlAbnzp3ThAkTNGXKFHl6euqnn35SYGCgvLy8tGDBAlWoUEFbtmxRenq6HB0d1b59exmNRq5vAAAAlDpkPZQlZD0AAMyLaSvAfWrevLmCg4P12WefacWKFUpMTJSNjY2ee+45nT9/Xp9//rkkycHBQZKUmpqqWrVqyd3dvdD70HmFpVu3bp3eeOMNOTs7m5bj8fX1VWhoqC5cuKCAgADdunVLHTt2VI8ePdSxY0fCGQAAAEotsh7KCrIeAADmx2AccB8yMzMlST169NDAgQP1xRdfKDo6WklJSWrXrp1sbW0VFRWlHTt2SJKSkpIUFRUlDw8PVa1atSSbDvwpGRkZysnJUXJyss6ePSsXFxdJt5c0eeKJJxQWFqZr166pa9euunXrVqFjCWcAAAAobch6KCvIegAAPBgsUwn8RQXXVV+4cKFSUlK0adMm3bp1S926ddP48eN1+fJlTZo0SRcuXFBOTo6qVKkiOzs7rV27VnZ2dqyrDotV1LX566+/ateuXQoKClKrVq0UGhoq6X+fhfj4eEVFRem9994jlAEAAKDUIuvBmpH1AAAoGQzGAfcpMjJSCxcu1HvvvacKFSroyJEj+uijj9S8eXONGTNGubm5OnHihE6ePKkaNWro+eefl9FoVHZ2tmxtbUu6+cBdCoazbdu26T//+Y98fHz03HPPqWLFioqNjVVQUJDatGmjuXPnSir8g4VEXQwAAACUfmQ9WBuyHgAAJYfBOOAvyu+QDhs2TLVq1dK4ceNM2zZt2qSQkBC1atVKQ4YMUY0aNQodS+cVlqpg0Jo9e7ZiY2Pl7u6uM2fOqHv37ho8eLA8PT0VGxur4OBgvfjii5ozZ04JtxoAAAAoPmQ9WCOyHgAAJYupWsB9yMzM1LVr1+Th4SFJysrKkp2dnTp37qyTJ09q9erVyszM1LBhw1SzZk3TcYQzWKr8cPbRRx9p69atWrRokRo3bqwpU6Zo06ZNMhgMGjx4sLp06SKDwaCJEyeqRo0aGj58eAm3HAAAACg+ZD1YG7IeAAAli8E44A+6c111g8Ege3t7NWrUSBs3btTAgQPl5eVl2q9SpUry8PCQk5OTqlevXoItB/64rKwsSdKBAwc0ZMgQNW7cWEeOHNGhQ4fUqlUrbdq0Sbm5uRoyZIi6dOmiihUrqnnz5iXcagAAAOCvI+uhLCDrAQBQsqgmDPwBBcNZTEyMQkNDFRYWJkmmmZB9+/bViRMndOPGDaWlpengwYPq2bOnpk6dKhsbG+Xm5pbgGQBF27FjhzZu3Khdu3ZJkuzs7HTjxg2dOnVKrq6uSkpK0rp169S+fXvNmzdP7du314YNGzRixAgdOXJELVu2lK2trbKzs0v4TAAAAIA/j6wHa0XWAwDAsvBkHPA78vLyTOFs1qxZWrt2rWrVqqXTp0/r22+/1cKFCxUUFKRZs2apZ8+eqlatmhwdHZWTkyN/f38ZDIa7ZloCliAgIECnTp1SUlKSbGxstHfvXs2aNUuVK1fWwIEDVadOHcXHxys5OVldunSRJDk7O6tu3bpq3ry5GjRoYHovCtQDAACgtCHrwVqR9QAAsDzcUYHfkb+u+rlz55SQkKDVq1fL09NTP/30kwIDAzVixAgtWLBAUVFR2rJli9LT0+Xo6Kj27dvLaDRSwBsWqXfv3srMzFR4eLhycnK0d+9erVixQjt37tRLL70kPz8/GQwGLV26VJ6enmrSpIkk6cyZM+rWrZtpO9c3AAAASiuyHqwRWQ8AAMvEYBzwB6xbt04bNmxQhQoV5O3tLRcXF/n6+io0NFRjxoxRQECAli1bpo4dOxY6js4rLFHv3r2VkZGhVatWycnJSZLk4OCgqKgoZWRkSPrfDxNOTk7au3evHnvsMW3evFk3btxQz549ZTAYlJeXx/UNAACAUo2sB2tC1gMAwHKxlgLwOzIyMpSTk6Pk5GSdPXtWLi4ukm4vafLEE08oLCxM165dU9euXXXr1q1Cx9J5haUZMGCAsrKytH79ejk5OSkzM1OS5OXlJR8fH1WuXLnQ/v3795enp6dWrlwpFxcXxcTEyNbWVjk5OaYQBwAAAJRGZD1YE7IeAACWjSfjgDvcuea/g4ODOnXqpHLlyikoKEhjxoxRaGioabaYr6+vZsyYoaioKJUrV64EWw78tqVLl+rAgQOaNGmS6ccDe3t7SdK0adN06NAhnT17Vj///LM8PT1Vp04d1a9fX8uXL1dOTo6cnZ1lMBiUnZ1N3QAAAACUOmQ9WCuyHgAAls+Ql5eXV9KNACxFwXC2bds2/ec//5GPj4+ee+45VaxYUbGxsQoKClKbNm00d+5cSbdnTRacNcZyJbBU586d0/Tp05WSkqKOHTuqT58+kqSRI0cqLi5Obm5uqlSpkhISEiTd/nHC2dlZw4YNM+1LgXoAAACURmQ9WDOyHgAAlo/BOOD/FAxas2fPVmxsrNzd3XXmzBl1795dgwcPlqenp2JjYxUcHKwXX3xRc+bMKeFWA3/O+fPnNW3aNCUnJ8vPz0979+7VTz/9pDlz5sjd3V2urq764YcflJSUpISEBP38888KDg5mdiQAAABKLbIeygKyHgAAlo3BOOAOH330kT744AO9//77aty4saZMmaJt27apS5cuGjx4sNzd3bVp0yZNnDhRw4cP1/Dhw0u6ycCfkh/Sjh49KoPBoA0bNsjd3f03j2G5EgAAAJR2ZD1YO7IeAACWi+fPgf+TlZWlrKwsHThwQEOGDFHjxo115MgRHTp0SK1atdKmTZu0dOlSXbp0SV26dNGSJUsUEBBQ0s0G/jRvb29NmTJFvr6+qly5sr788kvTtpycnCKPIZwBAACgtCLroawg6wEAYLkYjEOZtWPHDm3cuFG7du2SJNnZ2enGjRs6deqUXF1dlZSUpHXr1ql9+/aaN2+e2rdvrw0bNmjEiBE6cuSIWrZsKVtbW2VnZ5fwmQB/nqenpyZNmiR3d3etXbtWa9eulSQZjUbxwDQAAABKM7IeyjKyHgAAlonpLyiTAgICdOrUKSUlJcnGxkZ79+7VrFmzVLlyZQ0cOFB16tRRfHy8kpOT1aVLF0mSs7Oz6tatq+bNm6tBgwam92IWGUorb29vTZ48WdOmTVNsbKzS0tI0YMCAQkXqAQAAgNKErAeQ9QAAsEQ8GYcyp3fv3rpy5YrCw8O1evVqDRo0SHv27NHOnTslSX5+fvL19dWOHTvk6empJk2aSJLOnDmjbt26KTAwUEaj8Z5LPAClSX5IMxgMSkxMZKYkAAAASi2yHvA/ZD0AACwL07xQpvTu3VsZGRlatWqVnJycJEkODg6KiopSRkaGJJlmijk5OWnv3r167LHHtHnzZt24cUM9e/aUwWBQXl6ejEZjiZ0HUJy8vb01f/58Va5c2XR9M2MSAAAApQlZD7gbWQ8AAMvBk3EoMwYMGKCsrCytX79eTk5OyszMlCR5eXnJx8dHlStXLrR///795enpqZUrV8rFxUUxMTGytbVVTk4OnVdYnapVq8rGxka5ublc3wAAAChVyHrAvZH1AACwDDwZhzJh6dKlOnDggCZNmmSa5Whvby9JmjZtmg4dOqSzZ8/q559/lqenp+rUqaP69etr+fLlysnJkbOzswwGg7Kzs6kbAKtmY8McDQAAAJQeZD3gjyHrAQBQsgx5LBqNMuDcuXOaPn26UlJS1LFjR/Xp00eSNHLkSMXFxcnNzU2VKlVSQkKCpNvLmTg7O2vYsGGmfXNzc+m8AgAAAIAFIesBAACgNGAwDmXG+fPnNW3aNCUnJ8vPz0979+7VTz/9pDlz5sjd3V2urq764YcflJSUpISEBP38888KDg5mdiQAAAAAWDCyHgAAACwdg3EoU/JD2tGjR2UwGLRhwwa5u7v/5jEsVwIAAAAAlo2sBwAAAEvGOgwoU7y9vTVlyhT5+vqqcuXK+vLLL03bcnJyijyGcAYAAAAAlo2sBwAAAEvGk3Eok/JnTV69elWvvPKKevbsKUnKy8uTwWAo4dYBAAAAAP4Ksh4AAAAsEYNxKLPyQ1pKSoratWunAQMGlHSTAAAAAAD3iawHAAAAS8MylSizvL29NXnyZBkMBiUmJopxaQAAAAAo/ch6AAAAsDQ8GYcy7/Lly6pcubJsbGxYugQAAAAArARZDwAAAJaCwTjg/+Tm5srGhodFAQAAAMCakPUAAABQ0hiMAwAAAAAAAAAAAMyEqWEAAAAAAAAAAACAmTAYBwAAAAAAAAAAAJgJg3EAAAAAAAAAAACAmTAYBwAAAAAAAAAAAJgJg3EAAAAAAAAAAACAmTAYBwAAAAAAAAAAAJgJg3EAAJPw8HDVq1dP9erVU3R09G/u27p1a9WrV099+/Yt1jZ88803qlevnsLDw//S8X+0TfXq1dPjjz+uw4cP33Ofvn37ql69en+pHQAAAABgKch6hZH1AAAPGoNxAIAi7dy5857bDh8+rAsXLjzA1phHTk6O3nzzTWVkZJR0UwAAAADggSDrAQDw4DEYBwC4S82aNRUfH6+rV68Wuf2TTz5RpUqVHnCrzOPMmTN67733SroZAAAAAGB2ZD0AAEoGg3EAgLu0a9dOubm52rVr113b8vLytHPnTr300ksl0LLiVb9+fXl7e2vFihU6dOhQSTcHAAAAAMyKrAcAQMlgMA4AcJf/9//+nypWrFjk8iXx8fFKSkpS+/btizz2xo0bmjVrlv7+97+rQYMGatq0qcaMGaNTp07dte9//vMfBQQE6Omnn1aTJk00fvx4Xbt2rcj3PX36tMaMGaOmTZuqQYMGevHFFxUWFqb09PS/fJ7Ozs6aMWOG8vLy9NZbbyktLe13j8nKytIHH3ygbt266cknn1SDBg30/PPPa/LkyYXanl8PYdu2bVqwYIFat26thg0b6h//+Id27dql7OxsRUREqHXr1nriiSfUpUsX7d+//65/LyEhQQEBAXrmmWfUsGFDdejQQR9++KFycnL+8nkDAAAAKJvIevdG1gMAmJNtSTcAAGB5bGxs1KZNG23YsEFXr15V5cqVTdu2b98uDw8PPfXUU3cdd/XqVfXu3Vvnzp1T586d5evrq/Pnz2v16tXau3evli9friZNmkiSjh07Jn9/f9nb26tfv34qX768tmzZoj179tz1vgkJCRowYIBcXFzUp08fVaxYUYcPH9bixYv19ddfKyoqSg4ODn/pXP/2t7+pT58+WrVqlebNm6fJkyf/5v6BgYH67LPP1KVLF/Xo0UMZGRnav3+/1q9fr4sXL+rDDz8stP/cuXNVrlw59evXT1lZWVq2bJlGjx6tZs2a6eLFi+rXr5+ys7O1bNkyDR8+XJ988om8vb0lSZ999plGjRolb29vDR48WE5OToqLi9Ps2bP13XffKTw8XAaD4S+dNwAAAICyh6x3b2Q9AIA5MRgHACjSyy+/rLVr12rXrl3y8/OTdLsI9q5du9S5c+cig0FoaKj++9//asaMGerWrZvp9S5duqhLly566623tGPHDhmNRs2aNUuZmZlav369HnnkEUmSn5+fBgwYUGgZkfyZjK6urtq0aZPc3NxM+z799NOaPHmyoqKi9Oqrr/7lc33jjTe0f/9+rVq1Sm3bttXTTz9d5H4nTpzQnj171Ldv30JBrl+/furevbvi4uJ0/fp1UxslKTs7W+vXr5eLi4skyd7eXjNmzNCJEye0Y8cO0+vOzs5655139PXXX+uVV15RWlqaJk2aJB8fH61Zs0b29vaSJH9/f4WFhSkiIkI7duzQyy+//JfPGwAAAEDZQ9a7G1kPAGBuLFMJACjSM888o8qVKxdavuTAgQO6du1akcuW5NcdqFmzprp27VpoW926ddWpUyedPXtWx44dU0pKiuLj4/Xcc8+Zwpl0O7wMHDiw0LEnT55UYmKiWrZsqdzcXCUnJ5v+a9WqlRwcHLR79+77OlcnJyfNnDlTkjRx4kT9+uuvRe736KOP6tChQxozZkyh169duyZXV1dJuuvYFi1amEKYJNP5Pv/884Ver1mzpiQpKSlJkvSvf/1LKSkpatu2rW7dulXovPND2f2eNwAAAICyh6x3N7IeAMDceDIOAFAkGxsbtW3bVmvWrNG1a9dUqVIlffLJJ6pVq5bq169/1/4pKSm6efOmnn766SJnUtatW1eSdP78eRkMBuXm5ppCSUEFA5sknTlzRpK0Zs0arVmzpsi2Xrhw4U+f352aNGmivn37KioqSnPnztWUKVOK3M/e3l6ffPKJ4uLidO7cOZ0/f15XrlwxnXNubm6h/atUqVLob1tb2yJfNxqNkm7PDpX+d96hoaEKDQ0tsi3Fcd4AAAAAyhayHlkPAPDgMRgHALindu3aKTo6Wrt27VL37t21Z88e9enTp8h984PFvda1zw8u+UtwFDymqP3u/LtPnz564YUXinzv/NBzv8aMGaP9+/fr448/1osvvnjX9lu3bql///46duyYGjdurAYNGqhTp05q2LChVqxYoS1btvzhtv3e+v/55z1y5Eg9+eSTRe7j7Oz8e6cEAAAAAHch6xVG1gMAmBuDcQCAe2rcuLGqVq2qHTt2yMPDQ9evXy9y2RJJqlixolxcXPTjjz8qLy/vrgCSmJgoSfLw8JCXl5dsbGx06tSpu97n7Nmzhf7OL3AtSc2aNSu0LTc3V59++qmqV6/+l87vTuXKldOMGTPk7++vt956q1A9AEmKiorS999/r6CgIPXq1avQtqtXrxZLG/Lln7ejo+Nd533r1i199dVXd824BAAAAIA/gqznVmg7WQ8AYG7UjAMA3FP+8iXx8fFavXq1Hn30UT388MP33LdNmzY6e/asYmNjC207deqUtm7dqurVq+vxxx+Xm5ubmjVrpri4OB0+fNi0X05Ojj766KNCxzZo0EBeXl7auHGj/vvf/xbatnbtWgUGBiomJqZ4Tli3Q2n//v114cIFHTt2rNC2lJQUSVK9evUKvf7vf/9b3377rekcisOzzz4rZ2dnRUZGmv7dfIsXL9aoUaO0b9++Yvm3AAAAAJQtZD2yHgDgweLJOADAb3r55Ze1cuVKffHFF3rjjTd+c9833nhDBw8e1KRJk/Ttt9+qUaNGOn/+vNasWSOj0agZM2aYZlFOnjxZvXr10sCBA+Xv72+alfnTTz8Vek+j0ahp06Zp6NCh6tq1q3r16qUaNWro6NGjiomJUY0aNfT6668X6zkHBgbqiy++MK3ln69169ZauXKlxo4dKz8/P5UvX17ff/+9Nm7cKKPRqKysLP3yyy/F0gZXV1dNmTJFEydO1D/+8Q/17NlTVatW1YEDB/TJJ5/I19dXfn5+xfJvAQAAACh7yHr/Q9YDAJgbg3EAgN/05JNPysPDQz///LNefvnl39y3SpUq2rBhgxYtWqS9e/dq27ZtcnNzU+vWrRUQEFBopmXt2rW1bt06vffee1q3bp0yMzPVrFkzjRo1Sv369Sv0vs2aNdO6desUERGhmJgY3bx5U+7u7vLz89PQoUOLfQkPR0dHzZw5U35+foXqGjRt2lShoaFatmyZFixYIHt7e3l6eiowMFCPPPKIhgwZoi+//FINGzYslnZ07txZHh4eWr58uaKiopSRkSFPT0+99tprGjRokJycnIrl3wEAAABQ9pD1yHoAgAfHkFdURVUAAAAAAAAAAAAA942acQAAAAAAAAAAAICZMBgHAAAAAAAAAAAAmAmDcQAAAAAAAAAAAICZMBgHAAAAAAAAAAAAmAmDcQAAAAAAAAAAAICZMBgHAAAAAAAAAAAAmAmDcQAAAAAAAAAAAICZMBgHAAAAAAAAAAAAmAmDcQAAAAAAAAAAAICZMBgHAAAAAAAAAAAAmAmDcQAAAAAAAAAAAICZMBgHAAAAAAAAAAAAmMn/Bxhl0aIXuXp/AAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1800x1400 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import matplotlib\n",
    "\n",
    "from sklearn.model_selection import train_test_split, GridSearchCV, cross_val_score\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.ensemble import RandomForestRegressor\n",
    "from sklearn.metrics import mean_squared_error, mean_absolute_error, r2_score\n",
    "from sklearn.feature_selection import SelectFromModel\n",
    "\n",
    "\n",
    "evaluation_data = {\n",
    "    'Model Name': [\n",
    "        'Linear Regression (Remove Apparent Temperature (C))',\n",
    "        'Random Forest Regression (Remove Highly Correlated Features)',\n",
    "        'Random Forest Regression (Include Apparent Temperature (C))',\n",
    "        'Linear Regression (Include Apparent Temperature (C))'\n",
    "    ],\n",
    "    'MSE': [34.3205, 2.6677, 0.0024, 0.8961],\n",
    "    'RMSE': [5.8584, 1.6333, 0.0494, 0.9466],\n",
    "    'MAE': [4.7881, 1.1897, 0.0136, 0.7406],\n",
    "    'R² Score': [0.6231, 0.9707, 1.0000, 0.9902]\n",
    "}\n",
    "\n",
    "# Create DataFrame\n",
    "evaluation_df = pd.DataFrame(evaluation_data)\n",
    "\n",
    "# Set Model Name as index\n",
    "evaluation_df.set_index('Model Name', inplace=True)\n",
    "\n",
    "# Display the table\n",
    "print(evaluation_df)\n",
    "\n",
    "# Set Seaborn plot style\n",
    "sns.set(style=\"whitegrid\")\n",
    "\n",
    "# Create four subplots\n",
    "fig, axes = plt.subplots(2, 2, figsize=(18, 14))  # Increased figure size for better readability\n",
    "axes = axes.flatten()\n",
    "\n",
    "# Define metrics to plot\n",
    "metrics = ['MSE', 'RMSE', 'MAE', 'R² Score']\n",
    "\n",
    "for i, metric in enumerate(metrics):\n",
    "    sns.barplot(\n",
    "        x=evaluation_df.index,\n",
    "        y=evaluation_df[metric],\n",
    "        ax=axes[i]\n",
    "        # palette='Set2'  # Removed to prevent FutureWarning\n",
    "    )\n",
    "    axes[i].set_title(f'{metric} Comparison', fontsize=18)\n",
    "    axes[i].set_ylabel(metric, fontsize=14)\n",
    "    axes[i].set_xlabel('Model Name', fontsize=14)\n",
    "    for label in axes[i].get_xticklabels():\n",
    "        label.set_rotation(45)  # Rotate x-axis labels to prevent overlap\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 二、已知多变量对离散单变量的预测\n",
    "\n",
    "**目标变量**: Summary(天气摘要)Summary 是一个描述天气状况的分类变量，因此我们可以将其视为**多分类问题**。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "模型准确率：0.6936\n",
      "\n",
      "分类报告：\n",
      "                          precision    recall  f1-score   support\n",
      "\n",
      "                  Breezy       1.00      0.44      0.62         9\n",
      "          Breezy and Dry       0.00      0.00      0.00         1\n",
      "        Breezy and Foggy       0.75      1.00      0.86         6\n",
      "Breezy and Mostly Cloudy       0.55      0.53      0.54       116\n",
      "     Breezy and Overcast       0.62      0.78      0.69        94\n",
      "Breezy and Partly Cloudy       0.71      0.64      0.67        83\n",
      "                   Clear       0.73      0.52      0.61      2162\n",
      "                 Drizzle       1.00      0.57      0.73         7\n",
      "                     Dry       1.00      0.29      0.44         7\n",
      "   Dry and Mostly Cloudy       0.00      0.00      0.00         4\n",
      "   Dry and Partly Cloudy       0.86      0.35      0.50        17\n",
      "                   Foggy       1.00      1.00      1.00      1396\n",
      " Humid and Mostly Cloudy       0.00      0.00      0.00         4\n",
      "      Humid and Overcast       0.00      0.00      0.00         1\n",
      " Humid and Partly Cloudy       0.00      0.00      0.00         9\n",
      "              Light Rain       1.00      0.20      0.33         5\n",
      "           Mostly Cloudy       0.65      0.61      0.63      5754\n",
      "                Overcast       0.74      0.69      0.71      3317\n",
      "           Partly Cloudy       0.65      0.77      0.70      6261\n",
      "                    Rain       0.00      0.00      0.00         1\n",
      "                   Windy       1.00      1.00      1.00         1\n",
      "           Windy and Dry       0.00      0.00      0.00         1\n",
      "         Windy and Foggy       0.00      0.00      0.00         1\n",
      " Windy and Mostly Cloudy       0.50      0.22      0.31         9\n",
      "      Windy and Overcast       1.00      0.57      0.73        14\n",
      " Windy and Partly Cloudy       0.50      1.00      0.67         6\n",
      "\n",
      "                accuracy                           0.69     19286\n",
      "               macro avg       0.55      0.43      0.45     19286\n",
      "            weighted avg       0.70      0.69      0.69     19286\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\ProgramData\\anaconda3\\Lib\\site-packages\\sklearn\\metrics\\_classification.py:1509: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, f\"{metric.capitalize()} is\", len(result))\n",
      "c:\\ProgramData\\anaconda3\\Lib\\site-packages\\sklearn\\metrics\\_classification.py:1509: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, f\"{metric.capitalize()} is\", len(result))\n",
      "c:\\ProgramData\\anaconda3\\Lib\\site-packages\\sklearn\\metrics\\_classification.py:1509: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, f\"{metric.capitalize()} is\", len(result))\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "# 可视化库\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "# 机器学习库\n",
    "from sklearn.model_selection import train_test_split, GridSearchCV\n",
    "from sklearn.preprocessing import StandardScaler, LabelEncoder\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.metrics import accuracy_score, classification_report\n",
    "\n",
    "# 设置中文字体（如果需要显示中文）\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']\n",
    "plt.rcParams['axes.unicode_minus'] = False\n",
    "\n",
    "# 1. 加载数据\n",
    "data = pd.read_csv('weatherHistory.csv')\n",
    "\n",
    "# 2. 数据预处理\n",
    "# 转换日期时间格式\n",
    "data['Formatted Date'] = pd.to_datetime(data['Formatted Date'], utc=True)\n",
    "\n",
    "# 提取时间特征\n",
    "data['Year'] = data['Formatted Date'].dt.year\n",
    "data['Month'] = data['Formatted Date'].dt.month\n",
    "data['Day'] = data['Formatted Date'].dt.day\n",
    "data['Hour'] = data['Formatted Date'].dt.hour\n",
    "data['Weekday'] = data['Formatted Date'].dt.weekday\n",
    "\n",
    "# 删除原始日期列和 'Daily Summary'\n",
    "data = data.drop(['Formatted Date', 'Daily Summary'], axis=1)\n",
    "\n",
    "# 处理目标变量 'Summary'\n",
    "label_encoder = LabelEncoder()\n",
    "data['Summary_encoded'] = label_encoder.fit_transform(data['Summary'])\n",
    "\n",
    "# 处理 'Precip Type' 的缺失值\n",
    "data['Precip Type'] = data['Precip Type'].fillna('unknown')\n",
    "\n",
    "# 独热编码 'Precip Type'\n",
    "data = pd.get_dummies(data, columns=['Precip Type'], prefix='PrecipType')\n",
    "\n",
    "# 删除高度相关的特征，避免数据泄露\n",
    "data = data.drop(['Temperature (C)', 'Apparent Temperature (C)'], axis=1)\n",
    "\n",
    "# 删除原始的 'Summary' 列\n",
    "data = data.drop(['Summary'], axis=1)\n",
    "\n",
    "# 3. 数据集划分\n",
    "X = data.drop(['Summary_encoded'], axis=1)\n",
    "y = data['Summary_encoded']\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.20, random_state=42)\n",
    "\n",
    "# 4. 特征缩放\n",
    "numeric_features = ['Humidity', 'Wind Speed (km/h)', 'Wind Bearing (degrees)',\n",
    "                    'Visibility (km)', 'Pressure (millibars)', 'Year', 'Month',\n",
    "                    'Day', 'Hour', 'Weekday']\n",
    "\n",
    "scaler = StandardScaler()\n",
    "X_train[numeric_features] = scaler.fit_transform(X_train[numeric_features])\n",
    "X_test[numeric_features] = scaler.transform(X_test[numeric_features])\n",
    "\n",
    "# 5. 模型训练\n",
    "rf_classifier = RandomForestClassifier(n_estimators=100, random_state=42, n_jobs=-1)\n",
    "rf_classifier.fit(X_train, y_train)\n",
    "\n",
    "# 6. 模型评估\n",
    "y_pred = rf_classifier.predict(X_test)\n",
    "accuracy = accuracy_score(y_test, y_pred)\n",
    "print(f'模型准确率：{accuracy:.4f}')\n",
    "\n",
    "print(\"\\n分类报告：\")\n",
    "# 修改部分：获取实际存在的标签和对应的类别名称\n",
    "import numpy as np\n",
    "\n",
    "# 获取预测和真实值中的所有标签\n",
    "labels = np.unique(np.concatenate((y_test, y_pred)))\n",
    "target_names = label_encoder.inverse_transform(labels)\n",
    "\n",
    "# 生成分类报告\n",
    "print(classification_report(y_test, y_pred, labels=labels, target_names=target_names))\n",
    "\n",
    "# 7. 特征重要性分析\n",
    "importances = rf_classifier.feature_importances_\n",
    "feature_names = X_train.columns\n",
    "feature_importances = pd.DataFrame({'Feature': feature_names, 'Importance': importances})\n",
    "feature_importances = feature_importances.sort_values(by='Importance', ascending=False)\n",
    "\n",
    "plt.figure(figsize=(12, 8))\n",
    "sns.barplot(x='Importance', y='Feature', data=feature_importances)\n",
    "plt.title('特征重要性（随机森林分类器）')\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "模型准确率只有0.6936。\n",
    "\n",
    "因而需要通过**超参数**优化区进行调优，超参数则是在算法运行之前手动设置的参数，用于控制模型的行为和性能。\n",
    "\n",
    "这些超参数的选择会影响到模型的训练速度、收敛性、容量和泛化能力等方面。\n",
    "\n",
    "例如，学习率、迭代次数、正则化参数、隐藏层的神经元数量等都是常见的超参数。\n",
    "\n",
    "超参数的选择通常是一个试错的过程，需要根据经验和领域知识进行调整。\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 3 folds for each of 48 candidates, totalling 144 fits\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\ProgramData\\anaconda3\\Lib\\site-packages\\sklearn\\model_selection\\_split.py:737: UserWarning: The least populated class in y has only 1 members, which is less than n_splits=3.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "最佳参数：{'bootstrap': False, 'max_depth': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'n_estimators': 200}\n",
      "优化后模型准确率：0.7138\n",
      "\n",
      "优化后模型的分类报告：\n",
      "                          precision    recall  f1-score   support\n",
      "\n",
      "                  Breezy       1.00      0.56      0.71         9\n",
      "          Breezy and Dry       0.00      0.00      0.00         1\n",
      "        Breezy and Foggy       0.86      1.00      0.92         6\n",
      "Breezy and Mostly Cloudy       0.53      0.47      0.50       116\n",
      "     Breezy and Overcast       0.63      0.80      0.70        94\n",
      "Breezy and Partly Cloudy       0.63      0.63      0.63        83\n",
      "                   Clear       0.74      0.57      0.64      2162\n",
      "                 Drizzle       0.80      0.57      0.67         7\n",
      "                     Dry       1.00      0.29      0.44         7\n",
      "   Dry and Mostly Cloudy       0.00      0.00      0.00         4\n",
      "   Dry and Partly Cloudy       0.80      0.47      0.59        17\n",
      "                   Foggy       1.00      1.00      1.00      1396\n",
      " Humid and Mostly Cloudy       0.00      0.00      0.00         4\n",
      "      Humid and Overcast       0.00      0.00      0.00         1\n",
      " Humid and Partly Cloudy       0.00      0.00      0.00         9\n",
      "              Light Rain       1.00      0.40      0.57         5\n",
      "           Mostly Cloudy       0.67      0.64      0.66      5754\n",
      "                Overcast       0.76      0.72      0.74      3317\n",
      "           Partly Cloudy       0.67      0.77      0.72      6261\n",
      "                    Rain       0.00      0.00      0.00         1\n",
      "                   Windy       1.00      1.00      1.00         1\n",
      "           Windy and Dry       0.00      0.00      0.00         1\n",
      "         Windy and Foggy       0.00      0.00      0.00         1\n",
      " Windy and Mostly Cloudy       0.33      0.22      0.27         9\n",
      "      Windy and Overcast       0.88      0.50      0.64        14\n",
      " Windy and Partly Cloudy       0.50      0.83      0.62         6\n",
      "\n",
      "                accuracy                           0.71     19286\n",
      "               macro avg       0.53      0.44      0.46     19286\n",
      "            weighted avg       0.72      0.71      0.71     19286\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\ProgramData\\anaconda3\\Lib\\site-packages\\sklearn\\metrics\\_classification.py:1509: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, f\"{metric.capitalize()} is\", len(result))\n",
      "c:\\ProgramData\\anaconda3\\Lib\\site-packages\\sklearn\\metrics\\_classification.py:1509: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, f\"{metric.capitalize()} is\", len(result))\n",
      "c:\\ProgramData\\anaconda3\\Lib\\site-packages\\sklearn\\metrics\\_classification.py:1509: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, f\"{metric.capitalize()} is\", len(result))\n"
     ]
    }
   ],
   "source": [
    "# 8. 超参数调优\n",
    "param_grid = {\n",
    "    'n_estimators': [100, 200],\n",
    "    'max_depth': [None, 10, 20],\n",
    "    'min_samples_split': [2, 5],\n",
    "    'min_samples_leaf': [1, 2],\n",
    "    'bootstrap': [True, False]\n",
    "}\n",
    "\n",
    "rf = RandomForestClassifier(random_state=42, n_jobs=-1)\n",
    "grid_search = GridSearchCV(estimator=rf, param_grid=param_grid,\n",
    "                           cv=3, n_jobs=-1, verbose=2, scoring='accuracy')\n",
    "\n",
    "grid_search.fit(X_train, y_train)\n",
    "print(f'最佳参数：{grid_search.best_params_}')\n",
    "\n",
    "best_rf_classifier = grid_search.best_estimator_\n",
    "y_pred_best = best_rf_classifier.predict(X_test)\n",
    "accuracy_best = accuracy_score(y_test, y_pred_best)\n",
    "print(f'优化后模型准确率：{accuracy_best:.4f}')\n",
    "\n",
    "print(\"\\n优化后模型的分类报告：\")\n",
    "# 修改部分：获取实际存在的标签和对应的类别名称\n",
    "labels_best = np.unique(np.concatenate((y_test, y_pred_best)))\n",
    "target_names_best = label_encoder.inverse_transform(labels_best)\n",
    "\n",
    "# 生成分类报告\n",
    "print(classification_report(y_test, y_pred_best, labels=labels_best, target_names=target_names_best))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "初始模型准确率：0.6936\n",
    "\n",
    "优化后模型准确率：0.7138\n",
    "\n",
    "模型的整体准确率从 69.36% 提升到了 71.38%，这表明经过超参数调优后，模型的性能有所提升。\n",
    "\n",
    "**少数类别**的性能\n",
    "\n",
    "对于一些少数类别，如 'Breezy and Dry'、'Dry and Mostly Cloudy'、'Humid and Mostly Cloudy' 等，precision 和 recall 都为 0，这意味着模型无法正确预测这些类别。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\ProgramData\\anaconda3\\Lib\\site-packages\\sklearn\\metrics\\_ranking.py:1146: UndefinedMetricWarning: No positive samples in y_true, true positive value should be meaningless\n",
      "  warnings.warn(\n",
      "c:\\ProgramData\\anaconda3\\Lib\\site-packages\\sklearn\\metrics\\_ranking.py:1146: UndefinedMetricWarning: No positive samples in y_true, true positive value should be meaningless\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.metrics import roc_curve, auc\n",
    "from sklearn.preprocessing import label_binarize\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# 初始模型\n",
    "classes = rf_classifier.classes_\n",
    "n_classes = len(classes)\n",
    "y_test_binarized = label_binarize(y_test, classes=classes)\n",
    "y_score = rf_classifier.predict_proba(X_test)\n",
    "\n",
    "fpr = dict()\n",
    "tpr = dict()\n",
    "roc_auc = dict()\n",
    "\n",
    "for i in range(n_classes):\n",
    "    fpr[i], tpr[i], _ = roc_curve(y_test_binarized[:, i], y_score[:, i])\n",
    "    roc_auc[i] = auc(fpr[i], tpr[i])\n",
    "\n",
    "fpr[\"micro\"], tpr[\"micro\"], _ = roc_curve(y_test_binarized.ravel(), y_score.ravel())\n",
    "roc_auc[\"micro\"] = auc(fpr[\"micro\"], tpr[\"micro\"])\n",
    "\n",
    "# 优化后模型\n",
    "classes_best = best_rf_classifier.classes_\n",
    "n_classes_best = len(classes_best)\n",
    "y_test_binarized_best = label_binarize(y_test, classes=classes_best)\n",
    "y_score_best = best_rf_classifier.predict_proba(X_test)\n",
    "\n",
    "fpr_best = dict()\n",
    "tpr_best = dict()\n",
    "roc_auc_best = dict()\n",
    "\n",
    "for i in range(n_classes_best):\n",
    "    fpr_best[i], tpr_best[i], _ = roc_curve(y_test_binarized_best[:, i], y_score_best[:, i])\n",
    "    roc_auc_best[i] = auc(fpr_best[i], tpr_best[i])\n",
    "\n",
    "fpr_best[\"micro\"], tpr_best[\"micro\"], _ = roc_curve(y_test_binarized_best.ravel(), y_score_best.ravel())\n",
    "roc_auc_best[\"micro\"] = auc(fpr_best[\"micro\"], tpr_best[\"micro\"])\n",
    "\n",
    "# 绘制 ROC 曲线\n",
    "plt.figure(figsize=(10, 8))\n",
    "\n",
    "plt.plot(fpr[\"micro\"], tpr[\"micro\"],\n",
    "         label='初始模型 ROC 曲线 (AUC = {0:0.4f})'.format(roc_auc[\"micro\"]),\n",
    "         color='navy', linestyle=':', linewidth=4)\n",
    "\n",
    "plt.plot(fpr_best[\"micro\"], tpr_best[\"micro\"],\n",
    "         label='优化后模型 ROC 曲线 (AUC = {0:0.4f})'.format(roc_auc_best[\"micro\"]),\n",
    "         color='darkorange', linestyle=':', linewidth=4)\n",
    "\n",
    "plt.plot([0, 1], [0, 1], 'k--', linewidth=2)\n",
    "\n",
    "plt.xlim([0.0, 1.0])\n",
    "plt.ylim([0.0, 1.05])\n",
    "plt.xlabel('假正率 (False Positive Rate)')\n",
    "plt.ylabel('真正率 (True Positive Rate)')\n",
    "plt.title('初始模型和优化后模型的 ROC 曲线对比')\n",
    "plt.legend(loc=\"lower right\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "在进行超参数优化之后，可以注意到模型的能力有所提升，从优化前的0.9878提升到了0.9893。\n",
    "\n",
    "\n",
    "## 2.1. **准确度（Accuracy）公式**：\n",
    "\n",
    "准确度衡量模型预测正确的比例，计算公式为：\n",
    "\n",
    "\\[\n",
    "\\text{Accuracy} = \\frac{\\text{TP} + \\text{TN}}{\\text{TP} + \\text{TN} + \\text{FP} + \\text{FN}}\n",
    "\\]\n",
    "\n",
    "- **TP**（True Positive，真正类）：预测为正类且实际为正类的数量。\n",
    "- **TN**（True Negative，真负类）：预测为负类且实际为负类的数量。\n",
    "- **FP**（False Positive，假正类）：预测为正类但实际为负类的数量。\n",
    "- **FN**（False Negative，假负类）：预测为负类但实际为正类的数量。\n",
    "\n",
    "\n",
    "**注意**：准确度并不能总是反映模型的整体表现，特别是在类别不平衡的数据集中。\n",
    "\n",
    "\n",
    "## 2.2. **ROC-AUC 曲线**：\n",
    "ROC 曲线（Receiver Operating Characteristic Curve）表示在不同的分类阈值下，模型的 **假正率**（FPR）和 **真正率**（TPR）之间的关系。\n",
    "\n",
    "- **TPR（True Positive Rate，真正率）**，即 **召回率（Recall）**，计算公式为：\n",
    "\n",
    "\\[\n",
    "\\text{TPR} = \\frac{\\text{TP}}{\\text{TP} + \\text{FN}}\n",
    "\\]\n",
    "\n",
    "- **FPR（False Positive Rate，假正率）**，计算公式为：\n",
    "\n",
    "\\[\n",
    "\\text{FPR} = \\frac{\\text{FP}}{\\text{FP} + \\text{TN}}\n",
    "\\]\n",
    "\n",
    "- **AUC（Area Under Curve）**：即 ROC 曲线下的面积，表示模型区分正负类能力的一个综合指标。AUC 值越接近 1，模型的区分能力越强；若 AUC=0.5，则模型的表现与随机猜测没有区别。\n",
    "\n",
    "## 2.3. **多分类问题下 TPR 和 FPR 的计算**：\n",
    "对于多分类问题，通常使用 **\"一对多\"（One-vs-Rest, OvR）** 的方法来计算 TPR 和 FPR。\n",
    "\n",
    "## **真正率 (TPR) 公式**：\n",
    "每个类别的真正率（Recall）是在将该类别作为正类时的召回率，公式为：\n",
    "\n",
    "\\[\n",
    "\\text{TPR}_i = \\frac{\\text{TP}_i}{\\text{TP}_i + \\text{FN}_i}\n",
    "\\]\n",
    "\n",
    "其中：\n",
    "- **TP** 是第 \\(i\\) 类的真正类（预测为第 \\(i\\) 类且实际为第 \\(i\\) 类的样本数）。\n",
    "- **FN** 是第 \\(i\\) 类的假负类（实际为第 \\(i\\) 类但预测为其他类的样本数）。\n",
    "\n",
    "### **假正率 (FPR) 公式**：\n",
    "假正率是将其他所有类别作为负类时的错误率，公式为：\n",
    "\n",
    "\\[\n",
    "\\text{FPR}_i = \\frac{\\text{FP}_i}{\\text{FP}_i + \\text{TN}_i}\n",
    "\\]\n",
    "\n",
    "其中：\n",
    "- **FP** 是第 \\(i\\) 类的假正类（实际为其他类别但预测为第 \\(i\\) 类的样本数）。\n",
    "- **TN** 是第 \\(i\\) 类的真负类（实际为其他类别且预测也为其他类别的样本数）。\n",
    "\n",
    "## 2.4. **多分类问题的 ROC-AUC 计算**：\n",
    "\n",
    "通常有两种方法来计算多分类问题的 AUC 值：\n",
    "\n",
    "### **(1) 宏平均（Macro-Averaging）**：\n",
    "对每个类别的 AUC 值进行简单平均：\n",
    "\n",
    "\\[\n",
    "\\text{AUC}_{macro} = \\frac{1}{n} \\sum_{i=1}^{n} \\text{AUC}_i\n",
    "\\]\n",
    "\n",
    "### **(2) 微平均（Micro-Averaging）**：\n",
    "将每个类别的 TP、FP、TN 和 FN 累加起来，计算整体的 TPR 和 FPR，绘制整体的 ROC 曲线并计算 AUC 值：\n",
    "\n",
    "\\[\n",
    "\\text{AUC}_{micro} = \\text{ROC曲线下的面积 (基于所有类别的预测结果)}\n",
    "\\]\n",
    "\n",
    "\n",
    "### **同样，ROC-AUC曲线也有一个严重的问题，精确率为 0 对 AUC 没有很大影响**"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "base",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
